Knowledge MCP
A high-precision local knowledge base server enabling AI agents to navigate, search, and reason about complex codebases using hybrid semantic, lexical, and graph retrieval.
README
Knowledge MCP
A high-precision local knowledge base server (RAG) that implements the Model Context Protocol (MCP). It enables AI agents (Codex, Claude Code, Gemini CLI, etc.) to navigate, search, and reason about complex codebases using a hybrid approach combining semantic, lexical, and structural analysis.
🚀 Key Features
- Hybrid Triple Search: Fuses three distinct retrieval channels through Reciprocal Rank Fusion (RRF) for maximum recall:
- Full-Text Search (FTS5): Handles exact name matches and specific keywords.
- Semantic Vector Search (
sqlite-vec): Understands concepts and natural language intent. - Graph-Based Retrieval: Provides a 2x relevance boost to actual code symbols and their relationships.
- Deep Semantic Indexing:
- C# / .NET: Integrated Roslyn analysis for precise symbol extraction and dependency graphs.
- Polyglot Support: Tree-sitter integration for high-quality parsing of TS, JS, Python, Go, and more.
- Markdown: Section-aware chunking for documentation.
- Knowledge Graph: Tracks relationships between symbols:
CALLS,INHERITS,IMPLEMENTS, andIMPORTS. Supports recursive Impact Analysis to estimate the blast radius of code changes. - Autonomous Embeddings: In-process generation using
sentence-transformers(mpnet-base-v2). Works natively inside Docker without external API dependencies. - Incremental Sync: Delta-sync mechanism via
mtimeandSHA-256ensures only modified files are processed, significantly speeding up updates.
🛠 Available MCP Tools
Search & Retrieval
knowledge_search: Triple hybrid search across all repositories. Returns chunks with trust levels (verifiedfor code,hintfor docs).knowledge_get_chunk: Retrieve detailed content and metadata for a specific knowledge chunk.
Symbol & Graph Navigation
knowledge_find_symbol: Locate classes, methods, and interfaces using wildcards (e.g.,*Repository).knowledge_get_callers/knowledge_get_callees: Navigate the call graph of any symbol.knowledge_get_hierarchy: Explore inheritance and interface implementations.knowledge_impact_analysis: Perform recursive dependency analysis to find everything affected by a symbol change.
Management
knowledge_sync_repo: Trigger a background delta-sync for a repository to update the AI's "memory" after code changes.knowledge_delete_repo: Wipe all indexed data for a specific repository.
📋 Requirements
- Python 3.10+
- .NET 8.0 SDK (Required for Roslyn-based C# analysis)
- Docker (Recommended for easiest deployment)
🐳 Quick Start (Docker)
1. Configure your repository path
Create a .env file in the project root:
# The host directory that will be mounted as /repos inside the container.
# Set this to the PARENT folder of your repositories.
REPOS_DIR=C:\Repos
2. Build and start the container
docker compose up -d
3. Index a specific project
Option A — PowerShell script (recommended, see Scripts):
.\scripts\Reindex-Repo.ps1 -Wait
Option B — direct HTTP call:
curl -X POST http://localhost:8000/sync \
-H "Content-Type: application/json" \
-d '{"repo_id": "my-app", "repo_path": "/repos/my-app"}'
⚠️
repo_pathis the path inside the container (e.g.,/repos/my-app), not the host path.
4. Connect your MCP Client
Add this to your AI client's config (e.g., mcp.json):
{
"mcpServers": {
"knowledge-mcp": {
"command": "docker",
"args": ["exec", "-i", "knowledge-mcp", "python", "-m", "knowledge_mcp.main", "mcp"]
}
}
}
🔧 Scripts
scripts/Reindex-Repo.ps1
A PowerShell helper script that triggers re-indexing of a repository by sending a POST request to the running knowledge-mcp server.
Parameters:
| Parameter | Default | Description |
|---|---|---|
-RepoId |
ImpactOS.Core.Lib |
Unique repository identifier used as a key in the database |
-RepoPath |
/repos/ImpactOS.Core.Lib |
Path to the repository inside the Docker container |
-ServerUrl |
http://localhost:8000 |
URL of the running knowledge-mcp server |
-Wait |
$false |
If set, streams container logs after triggering sync |
Usage examples:
# Trigger re-indexing with default settings (ImpactOS.Core.Lib)
.\scripts\Reindex-Repo.ps1
# Trigger and watch progress in real time
.\scripts\Reindex-Repo.ps1 -Wait
# Index a different repository
.\scripts\Reindex-Repo.ps1 -RepoId "MyOtherLib" -RepoPath "/repos/MyOtherLib"
# Point to a remote server
.\scripts\Reindex-Repo.ps1 -ServerUrl "http://192.168.1.100:8000" -Wait
How it works:
- Verifies the server is reachable at
ServerUrl. - Sends a
POST /syncrequest withrepo_idandrepo_path. - Indexing runs in the background inside the container.
- With
-Wait, streams live logs viadocker logs -f.
💡 Path mapping: If
REPOS_DIR=C:\Repos, thenC:\Repos\MyLibon the host is accessible inside the container as/repos/MyLib.
📐 Architecture & Decisions
For deep dives into the technical design, see our Architecture Decision Records:
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.