KB MCP Server
An MCP server aimed to be portable, local, easy and convenient to support semantic/graph based retrieval of txtai 'all in one' embeddings database. Any txtai embeddings db in tar.gz form can be loaded
What is KB MCP Server?
KB MCP Server is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcp server aimed to be portable, local, easy and convenient to support semantic/graph based retrieval of txtai 'all in one' embeddings database. any txtai embeddings db in tar.gz form can be loaded
An MCP server aimed to be portable, local, easy and convenient to support semantic/graph based retrieval of txtai 'all in one' embeddings database. Any txtai embeddings db in tar.gz form can be loaded
This server falls under the Knowledge & Memory category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- An MCP server aimed to be portable, local, easy and convenie
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx kbConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use KB MCP Server
The KB MCP server provides AI assistants with semantic and graph-based retrieval over locally stored knowledge bases built on the txtai 'all-in-one' embeddings format. You can load any txtai embeddings database — packaged as a directory or compressed .tar.gz archive — and instantly query it through your MCP client using natural language. It supports hybrid search combining vector similarity and keyword matching, causal boosting for 'why/how' questions, and knowledge graph traversal, making it well-suited for private document collections, internal wikis, and research corpora.
Prerequisites
- Python 3.10 or later (3.10 recommended for compatibility)
- uv package manager (pip install -U uv) or conda environment manager
- A pre-built txtai embeddings database (directory or .tar.gz file) — build one with the kb-build command
- An MCP client such as Claude Desktop, Cursor, or any stdio-compatible client
Create a Python virtual environment
Use uv to create an isolated environment with Python 3.10. Activate it before proceeding.
pip install -U uv
uv venv --python=3.10
source .venv/bin/activateInstall kb-mcp-server
Install the kb-mcp-server package from PyPI into your virtual environment.
uv pip install kb-mcp-serverBuild a knowledge base from your documents
Use the kb-build utility to index your documents and export them as a portable .tar.gz archive. Provide a config.yml to control chunking, embedding model, and other options.
kb-build --input /path/to/documents --export knowledge_base.tar.gzVerify the knowledge base with a test search
Before connecting to an MCP client, confirm the knowledge base loads correctly and returns relevant results.
kb-search knowledge_base.tar.gz "What is the return policy?" --limit 5Configure your MCP client
Add the kb-mcp-server to your claude_desktop_config.json or equivalent config file, pointing to your knowledge base file.
Enable causal boosting (optional)
For better answers to 'why' and 'how' questions, start the server with the --enable-causal-boost flag or provide a custom boost configuration YAML.
kb-mcp-server --embeddings knowledge_base.tar.gz --enable-causal-boostKB MCP Server Examples
Client configuration
Add this to claude_desktop_config.json. The TXTAI_EMBEDDINGS environment variable can also be used instead of the --embeddings argument.
{
"mcpServers": {
"kb": {
"command": "uvx",
"args": [
"--from", "kb-mcp-server",
"kb-mcp-server",
"--embeddings", "/path/to/knowledge_base.tar.gz"
]
}
}
}Prompts to try
Once the server is loaded with your knowledge base, query it using natural language through your AI assistant.
- "Search the knowledge base for information about onboarding procedures"
- "Find documents related to the Q3 product roadmap"
- "Why did the project fail according to the post-mortem?"
- "Show me everything connected to the 'authentication' topic in the knowledge graph"
- "Summarize all documents about customer refund policies"Troubleshooting KB MCP Server
Server fails to start with 'embeddings not found' error
Make sure the path passed to --embeddings (or TXTAI_EMBEDDINGS) points to an actual directory or .tar.gz file created by kb-build. Relative paths can cause issues — use absolute paths.
Search returns empty or irrelevant results
The embedding model used to build the index must match the model used to query. If you used a custom model in kb-build, specify the same model in your config.yml when running kb-mcp-server.
Python version compatibility errors on install
This package requires Python 3.10 exactly for best compatibility. Use 'uv venv --python=3.10' to pin the version and ensure you are inside the activated venv before installing.
Frequently Asked Questions about KB MCP Server
What is KB MCP Server?
KB MCP Server is a Model Context Protocol (MCP) server that mcp server aimed to be portable, local, easy and convenient to support semantic/graph based retrieval of txtai 'all in one' embeddings database. any txtai embeddings db in tar.gz form can be loaded It connects AI assistants to external tools and data sources through a standardized interface.
How do I install KB MCP Server?
Follow the installation instructions on the KB MCP Server GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with KB MCP Server?
KB MCP Server works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is KB MCP Server free to use?
Yes, KB MCP Server is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.
KB MCP Server Alternatives — Similar Knowledge & Memory Servers
Looking for alternatives to KB MCP Server? Here are other popular knowledge & memory servers you can use with Claude, Cursor, and VS Code.
MemPalace
★ 52.6kA local AI memory system that stores all conversations verbatim and organizes them into navigable structures. It provides 19 MCP tools for AI assistants to search and retrieve past decisions, debugging sessions, and architecture debates automatically
Kratos
★ 25.7k🏛️ Memory System for AI Coding Tools - Never explain your codebase again. MCP server with perfect project isolation, 95.8% context accuracy, and the Four Pillars Framework.
Context Mode
★ 15.4kAn MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programm
Memu
★ 13.7kMemory for 24/7 proactive agents like OpenClaw.
MemOS
★ 9.3kMemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, u
Everos
★ 5.4kBuild, evaluate, and integrate long-term memory for self-evolving agents.
Browse More Knowledge & Memory MCP Servers
Explore all knowledge & memory servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up KB MCP Server in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
Ready to use KB MCP Server?
Browse our complete directory of 33,000+ MCP servers, read setup guides for your editor, and start building with the Model Context Protocol.