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LocalKB

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Before using LocalKB, download the required models to avoid startup delays:

pip install huggingface-hub
huggingface-cli download Qwen/Qwen3-Embedding-0.6B
huggingface-cli download Qwen/Qwen3-Reranker-0.6B

Expected timings, based on my M1 Max MacBook Pro:

  • The first use of add_text_to_kb or search_kb in a session will load the models into memory, taking roughly 10 extra seconds.
  • Searches take roughly 10 seconds (results are retrieved in about 0.5 seconds, then the reranker model spends about 1.5-2 seconds to score each result.)

Available Tools

Knowledge Base Management

list_kbs - List all available knowledge bases

  • No arguments

create_kb - Create a new knowledge base

  • kb_name (string): Name for the knowledge base
  • description (string): Description of the knowledge base

Content Management

add_text_to_kb - Add text content directly to a knowledge base

  • kb_name (string): Name of the knowledge base to add content to
  • source (string): Unique identifier for the text content (e.g., filename, document title)
  • text (string): The text content to add to the knowledge base
  • metadata (object, optional): Optional metadata dict to attach to all content

search_kb - Search for relevant content using semantic search

  • kb_name (string): Name of the knowledge base to search
  • query (string): Search query string
  • filters (object, optional): Optional ChromaDB metadata filters to narrow search

Add to Claude

Add to your Claude Code MCP configuration:

claude mcp add-json -s user LocalKB '{"command": "uvx", "args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]}'

Add to your Claude Desktop MCP configuration:

{
"mcpServers": {
"LocalKB": {
"command": "uvx",
"args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]
}
}
}

Manual Use

Command Line

Run this command to open an interactive menu with options to use the various tools:

uvx --from git+https://github.com/RoryMB/LocalKB@main localkb --cli

Python Import

Run Python files with this command if you do not want to clone the repo:

uv run --with git+https://github.com/RoryMB/LocalKB@main file.py

Example Python file:

fromlocalkb.toolsimport (
create_kb,
add_text_to_kb,
search_kb,
list_kbs
)
defmain():
# Create a knowledge baseresult=create_kb("my-docs", "Project documentation")
print(result)
# Add contentresult=add_text_to_kb(
"my-docs",
"installation-guide",
"To install this project, run: pip install -e ."
)
print(result)
# Search for contentresults=search_kb("my-docs", "how to install")
forresultinresults:
print(f"Content: {result['content']}")
print(f"Source: {result['metadata']['source']}")
# Run the functionmain()

About

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Resources

Stars

2 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
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LocalKB

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Before using LocalKB, download the required models to avoid startup delays:

pip install huggingface-hub
huggingface-cli download Qwen/Qwen3-Embedding-0.6B
huggingface-cli download Qwen/Qwen3-Reranker-0.6B

Expected timings, based on my M1 Max MacBook Pro:

  • The first use of add_text_to_kb or search_kb in a session will load the models into memory, taking roughly 10 extra seconds.
  • Searches take roughly 10 seconds (results are retrieved in about 0.5 seconds, then the reranker model spends about 1.5-2 seconds to score each result.)

Available Tools

Knowledge Base Management

list_kbs - List all available knowledge bases

  • No arguments

create_kb - Create a new knowledge base

  • kb_name (string): Name for the knowledge base
  • description (string): Description of the knowledge base

Content Management

add_text_to_kb - Add text content directly to a knowledge base

  • kb_name (string): Name of the knowledge base to add content to
  • source (string): Unique identifier for the text content (e.g., filename, document title)
  • text (string): The text content to add to the knowledge base
  • metadata (object, optional): Optional metadata dict to attach to all content

search_kb - Search for relevant content using semantic search

  • kb_name (string): Name of the knowledge base to search
  • query (string): Search query string
  • filters (object, optional): Optional ChromaDB metadata filters to narrow search

Add to Claude

Add to your Claude Code MCP configuration:

claude mcp add-json -s user LocalKB '{"command": "uvx", "args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]}'

Add to your Claude Desktop MCP configuration:

{
"mcpServers": {
"LocalKB": {
"command": "uvx",
"args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]
}
}
}

Manual Use

Command Line

Run this command to open an interactive menu with options to use the various tools:

uvx --from git+https://github.com/RoryMB/LocalKB@main localkb --cli

Python Import

Run Python files with this command if you do not want to clone the repo:

uv run --with git+https://github.com/RoryMB/LocalKB@main file.py

Example Python file:

fromlocalkb.toolsimport (
create_kb,
add_text_to_kb,
search_kb,
list_kbs
)
defmain():
# Create a knowledge baseresult=create_kb("my-docs", "Project documentation")
print(result)
# Add contentresult=add_text_to_kb(
"my-docs",
"installation-guide",
"To install this project, run: pip install -e ."
)
print(result)
# Search for contentresults=search_kb("my-docs", "how to install")
forresultinresults:
print(f"Content: {result['content']}")
print(f"Source: {result['metadata']['source']}")
# Run the functionmain()

About

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Resources

Stars

2 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

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14 Commits

Folders and files

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LocalKB

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Before using LocalKB, download the required models to avoid startup delays:

pip install huggingface-hub
huggingface-cli download Qwen/Qwen3-Embedding-0.6B
huggingface-cli download Qwen/Qwen3-Reranker-0.6B

Expected timings, based on my M1 Max MacBook Pro:

  • The first use of add_text_to_kb or search_kb in a session will load the models into memory, taking roughly 10 extra seconds.
  • Searches take roughly 10 seconds (results are retrieved in about 0.5 seconds, then the reranker model spends about 1.5-2 seconds to score each result.)

Available Tools

Knowledge Base Management

list_kbs - List all available knowledge bases

  • No arguments

create_kb - Create a new knowledge base

  • kb_name (string): Name for the knowledge base
  • description (string): Description of the knowledge base

Content Management

add_text_to_kb - Add text content directly to a knowledge base

  • kb_name (string): Name of the knowledge base to add content to
  • source (string): Unique identifier for the text content (e.g., filename, document title)
  • text (string): The text content to add to the knowledge base
  • metadata (object, optional): Optional metadata dict to attach to all content

search_kb - Search for relevant content using semantic search

  • kb_name (string): Name of the knowledge base to search
  • query (string): Search query string
  • filters (object, optional): Optional ChromaDB metadata filters to narrow search

Add to Claude

Add to your Claude Code MCP configuration:

claude mcp add-json -s user LocalKB '{"command": "uvx", "args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]}'

Add to your Claude Desktop MCP configuration:

{
"mcpServers": {
"LocalKB": {
"command": "uvx",
"args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]
}
}
}

Manual Use

Command Line

Run this command to open an interactive menu with options to use the various tools:

uvx --from git+https://github.com/RoryMB/LocalKB@main localkb --cli

Python Import

Run Python files with this command if you do not want to clone the repo:

uv run --with git+https://github.com/RoryMB/LocalKB@main file.py

Example Python file:

fromlocalkb.toolsimport (
create_kb,
add_text_to_kb,
search_kb,
list_kbs
)
defmain():
# Create a knowledge baseresult=create_kb("my-docs", "Project documentation")
print(result)
# Add contentresult=add_text_to_kb(
"my-docs",
"installation-guide",
"To install this project, run: pip install -e ."
)
print(result)
# Search for contentresults=search_kb("my-docs", "how to install")
forresultinresults:
print(f"Content: {result['content']}")
print(f"Source: {result['metadata']['source']}")
# Run the functionmain()

About

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Resources

Stars

2 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

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LocalKB

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Before using LocalKB, download the required models to avoid startup delays:

pip install huggingface-hub
huggingface-cli download Qwen/Qwen3-Embedding-0.6B
huggingface-cli download Qwen/Qwen3-Reranker-0.6B

Expected timings, based on my M1 Max MacBook Pro:

  • The first use of add_text_to_kb or search_kb in a session will load the models into memory, taking roughly 10 extra seconds.
  • Searches take roughly 10 seconds (results are retrieved in about 0.5 seconds, then the reranker model spends about 1.5-2 seconds to score each result.)

Available Tools

Knowledge Base Management

list_kbs - List all available knowledge bases

  • No arguments

create_kb - Create a new knowledge base

  • kb_name (string): Name for the knowledge base
  • description (string): Description of the knowledge base

Content Management

add_text_to_kb - Add text content directly to a knowledge base

  • kb_name (string): Name of the knowledge base to add content to
  • source (string): Unique identifier for the text content (e.g., filename, document title)
  • text (string): The text content to add to the knowledge base
  • metadata (object, optional): Optional metadata dict to attach to all content

search_kb - Search for relevant content using semantic search

  • kb_name (string): Name of the knowledge base to search
  • query (string): Search query string
  • filters (object, optional): Optional ChromaDB metadata filters to narrow search

Add to Claude

Add to your Claude Code MCP configuration:

claude mcp add-json -s user LocalKB '{"command": "uvx", "args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]}'

Add to your Claude Desktop MCP configuration:

{
"mcpServers": {
"LocalKB": {
"command": "uvx",
"args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]
}
}
}

Manual Use

Command Line

Run this command to open an interactive menu with options to use the various tools:

uvx --from git+https://github.com/RoryMB/LocalKB@main localkb --cli

Python Import

Run Python files with this command if you do not want to clone the repo:

uv run --with git+https://github.com/RoryMB/LocalKB@main file.py

Example Python file:

fromlocalkb.toolsimport (
create_kb,
add_text_to_kb,
search_kb,
list_kbs
)
defmain():
# Create a knowledge baseresult=create_kb("my-docs", "Project documentation")
print(result)
# Add contentresult=add_text_to_kb(
"my-docs",
"installation-guide",
"To install this project, run: pip install -e ."
)
print(result)
# Search for contentresults=search_kb("my-docs", "how to install")
forresultinresults:
print(f"Content: {result['content']}")
print(f"Source: {result['metadata']['source']}")
# Run the functionmain()

About

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Resources

Stars

2 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content

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14 Commits

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LocalKB

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Before using LocalKB, download the required models to avoid startup delays:

pip install huggingface-hub
huggingface-cli download Qwen/Qwen3-Embedding-0.6B
huggingface-cli download Qwen/Qwen3-Reranker-0.6B

Expected timings, based on my M1 Max MacBook Pro:

  • The first use of add_text_to_kb or search_kb in a session will load the models into memory, taking roughly 10 extra seconds.
  • Searches take roughly 10 seconds (results are retrieved in about 0.5 seconds, then the reranker model spends about 1.5-2 seconds to score each result.)

Available Tools

Knowledge Base Management

list_kbs - List all available knowledge bases

  • No arguments

create_kb - Create a new knowledge base

  • kb_name (string): Name for the knowledge base
  • description (string): Description of the knowledge base

Content Management

add_text_to_kb - Add text content directly to a knowledge base

  • kb_name (string): Name of the knowledge base to add content to
  • source (string): Unique identifier for the text content (e.g., filename, document title)
  • text (string): The text content to add to the knowledge base
  • metadata (object, optional): Optional metadata dict to attach to all content

search_kb - Search for relevant content using semantic search

  • kb_name (string): Name of the knowledge base to search
  • query (string): Search query string
  • filters (object, optional): Optional ChromaDB metadata filters to narrow search

Add to Claude

Add to your Claude Code MCP configuration:

claude mcp add-json -s user LocalKB '{"command": "uvx", "args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]}'

Add to your Claude Desktop MCP configuration:

{
"mcpServers": {
"LocalKB": {
"command": "uvx",
"args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]
}
}
}

Manual Use

Command Line

Run this command to open an interactive menu with options to use the various tools:

uvx --from git+https://github.com/RoryMB/LocalKB@main localkb --cli

Python Import

Run Python files with this command if you do not want to clone the repo:

uv run --with git+https://github.com/RoryMB/LocalKB@main file.py

Example Python file:

fromlocalkb.toolsimport (
create_kb,
add_text_to_kb,
search_kb,
list_kbs
)
defmain():
# Create a knowledge baseresult=create_kb("my-docs", "Project documentation")
print(result)
# Add contentresult=add_text_to_kb(
"my-docs",
"installation-guide",
"To install this project, run: pip install -e ."
)
print(result)
# Search for contentresults=search_kb("my-docs", "how to install")
forresultinresults:
print(f"Content: {result['content']}")
print(f"Source: {result['metadata']['source']}")
# Run the functionmain()

About

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Resources

Stars

2 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

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14 Commits

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LocalKB

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Before using LocalKB, download the required models to avoid startup delays:

pip install huggingface-hub
huggingface-cli download Qwen/Qwen3-Embedding-0.6B
huggingface-cli download Qwen/Qwen3-Reranker-0.6B

Expected timings, based on my M1 Max MacBook Pro:

  • The first use of add_text_to_kb or search_kb in a session will load the models into memory, taking roughly 10 extra seconds.
  • Searches take roughly 10 seconds (results are retrieved in about 0.5 seconds, then the reranker model spends about 1.5-2 seconds to score each result.)

Available Tools

Knowledge Base Management

list_kbs - List all available knowledge bases

  • No arguments

create_kb - Create a new knowledge base

  • kb_name (string): Name for the knowledge base
  • description (string): Description of the knowledge base

Content Management

add_text_to_kb - Add text content directly to a knowledge base

  • kb_name (string): Name of the knowledge base to add content to
  • source (string): Unique identifier for the text content (e.g., filename, document title)
  • text (string): The text content to add to the knowledge base
  • metadata (object, optional): Optional metadata dict to attach to all content

search_kb - Search for relevant content using semantic search

  • kb_name (string): Name of the knowledge base to search
  • query (string): Search query string
  • filters (object, optional): Optional ChromaDB metadata filters to narrow search

Add to Claude

Add to your Claude Code MCP configuration:

claude mcp add-json -s user LocalKB '{"command": "uvx", "args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]}'

Add to your Claude Desktop MCP configuration:

{
"mcpServers": {
"LocalKB": {
"command": "uvx",
"args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]
}
}
}

Manual Use

Command Line

Run this command to open an interactive menu with options to use the various tools:

uvx --from git+https://github.com/RoryMB/LocalKB@main localkb --cli

Python Import

Run Python files with this command if you do not want to clone the repo:

uv run --with git+https://github.com/RoryMB/LocalKB@main file.py

Example Python file:

fromlocalkb.toolsimport (
create_kb,
add_text_to_kb,
search_kb,
list_kbs
)
defmain():
# Create a knowledge baseresult=create_kb("my-docs", "Project documentation")
print(result)
# Add contentresult=add_text_to_kb(
"my-docs",
"installation-guide",
"To install this project, run: pip install -e ."
)
print(result)
# Search for contentresults=search_kb("my-docs", "how to install")
forresultinresults:
print(f"Content: {result['content']}")
print(f"Source: {result['metadata']['source']}")
# Run the functionmain()

About

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

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2 stars

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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LocalKB

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Before using LocalKB, download the required models to avoid startup delays:

pip install huggingface-hub
huggingface-cli download Qwen/Qwen3-Embedding-0.6B
huggingface-cli download Qwen/Qwen3-Reranker-0.6B

Expected timings, based on my M1 Max MacBook Pro:

  • The first use of add_text_to_kb or search_kb in a session will load the models into memory, taking roughly 10 extra seconds.
  • Searches take roughly 10 seconds (results are retrieved in about 0.5 seconds, then the reranker model spends about 1.5-2 seconds to score each result.)

Available Tools

Knowledge Base Management

list_kbs - List all available knowledge bases

  • No arguments

create_kb - Create a new knowledge base

  • kb_name (string): Name for the knowledge base
  • description (string): Description of the knowledge base

Content Management

add_text_to_kb - Add text content directly to a knowledge base

  • kb_name (string): Name of the knowledge base to add content to
  • source (string): Unique identifier for the text content (e.g., filename, document title)
  • text (string): The text content to add to the knowledge base
  • metadata (object, optional): Optional metadata dict to attach to all content

search_kb - Search for relevant content using semantic search

  • kb_name (string): Name of the knowledge base to search
  • query (string): Search query string
  • filters (object, optional): Optional ChromaDB metadata filters to narrow search

Add to Claude

Add to your Claude Code MCP configuration:

claude mcp add-json -s user LocalKB '{"command": "uvx", "args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]}'

Add to your Claude Desktop MCP configuration:

{
"mcpServers": {
"LocalKB": {
"command": "uvx",
"args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]
}
}
}

Manual Use

Command Line

Run this command to open an interactive menu with options to use the various tools:

uvx --from git+https://github.com/RoryMB/LocalKB@main localkb --cli

Python Import

Run Python files with this command if you do not want to clone the repo:

uv run --with git+https://github.com/RoryMB/LocalKB@main file.py

Example Python file:

fromlocalkb.toolsimport (
create_kb,
add_text_to_kb,
search_kb,
list_kbs
)
defmain():
# Create a knowledge baseresult=create_kb("my-docs", "Project documentation")
print(result)
# Add contentresult=add_text_to_kb(
"my-docs",
"installation-guide",
"To install this project, run: pip install -e ."
)
print(result)
# Search for contentresults=search_kb("my-docs", "how to install")
forresultinresults:
print(f"Content: {result['content']}")
print(f"Source: {result['metadata']['source']}")
# Run the functionmain()

About

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Resources

Stars

2 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
Skip to content

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14 Commits

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NameName
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LocalKB

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Before using LocalKB, download the required models to avoid startup delays:

pip install huggingface-hub
huggingface-cli download Qwen/Qwen3-Embedding-0.6B
huggingface-cli download Qwen/Qwen3-Reranker-0.6B

Expected timings, based on my M1 Max MacBook Pro:

  • The first use of add_text_to_kb or search_kb in a session will load the models into memory, taking roughly 10 extra seconds.
  • Searches take roughly 10 seconds (results are retrieved in about 0.5 seconds, then the reranker model spends about 1.5-2 seconds to score each result.)

Available Tools

Knowledge Base Management

list_kbs - List all available knowledge bases

  • No arguments

create_kb - Create a new knowledge base

  • kb_name (string): Name for the knowledge base
  • description (string): Description of the knowledge base

Content Management

add_text_to_kb - Add text content directly to a knowledge base

  • kb_name (string): Name of the knowledge base to add content to
  • source (string): Unique identifier for the text content (e.g., filename, document title)
  • text (string): The text content to add to the knowledge base
  • metadata (object, optional): Optional metadata dict to attach to all content

search_kb - Search for relevant content using semantic search

  • kb_name (string): Name of the knowledge base to search
  • query (string): Search query string
  • filters (object, optional): Optional ChromaDB metadata filters to narrow search

Add to Claude

Add to your Claude Code MCP configuration:

claude mcp add-json -s user LocalKB '{"command": "uvx", "args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]}'

Add to your Claude Desktop MCP configuration:

{
"mcpServers": {
"LocalKB": {
"command": "uvx",
"args": ["--from", "git+https://github.com/RoryMB/LocalKB@main", "localkb"]
}
}
}

Manual Use

Command Line

Run this command to open an interactive menu with options to use the various tools:

uvx --from git+https://github.com/RoryMB/LocalKB@main localkb --cli

Python Import

Run Python files with this command if you do not want to clone the repo:

uv run --with git+https://github.com/RoryMB/LocalKB@main file.py

Example Python file:

fromlocalkb.toolsimport (
create_kb,
add_text_to_kb,
search_kb,
list_kbs
)
defmain():
# Create a knowledge baseresult=create_kb("my-docs", "Project documentation")
print(result)
# Add contentresult=add_text_to_kb(
"my-docs",
"installation-guide",
"To install this project, run: pip install -e ."
)
print(result)
# Search for contentresults=search_kb("my-docs", "how to install")
forresultinresults:
print(f"Content: {result['content']}")
print(f"Source: {result['metadata']['source']}")
# Run the functionmain()

About

An MCP (Model Context Protocol) server for local knowledge base operations. LocalKB allows agents to create, manage, and search personal knowledge bases using semantic search and document chunking.

Resources

Stars

2 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages