What are the prerequisites for running CodeCompass?
You need Node.js v20+, Docker (for Qdrant), and Ollama installed. Optionally, a DeepSeek API key is required if you want to use cloud-based suggestions.
CodeCompass MCP Server
@alvinveroy
Basic information
About CodeCompass MCP Server
CodeCompass: AI-powered Vibe Coding with MCP. Connects Git repositories to AI assistants like Claude, using Ollama for privacy or OpenAI for cloud. Integrates with VSCode, Cursor, and more.
#nodejs#typescript#code-search#developer-tools#vscode-extension#qdrant#large-language-models#ollama#openai-integration#cursor-ai#ai-driven-development#model-context-protocol#mcp-server#vibe-coding#ai-coding-assistant#codebase-navigation#claude-integration#git-repository-analysis#autonomous-coding-assistance#privacy-focused-ai
CodeCompass MCP Server config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"CodeCompass": {
"command": "docker",
"args": [
"run",
"-p",
"6333:6333",
"-p",
"6334:6334",
"qdrant/qdrant"
]
}
}
}CodeCompass MCP Server tools
Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is CodeCompass?
CodeCompass helps developers tackle legacy or existing codebases by giving AI coding assistants the context they need for spot-on suggestions. It analyzes your codebase with Qdrant Vector Store and powers AI using Ollama (local) or cloud agents like DeepSeek, employing Agentic RAG to make suggestions smarter and more relevant. It is designed for developers working with messy, outdated, or poorly documented code who want to use AI-assisted development.
How to use CodeCompass?
Install prerequisites: Node.js v20+, Docker (for Qdrant), Ollama (with nomic-embed-text:v1.5 and optionally llama3.1:8b), and optionally a DeepSeek API key. Run npx -y @alvinveroy/codecompass@latest to install globally. Then start the server with codecompass [repoPath] [--port <number>] from the root of your git repository. You can also use CLI client mode to execute specific tools like agent_query, search_code, or switch_suggestion_model directly.
Key features of CodeCompass
- Maps repository structure and dependencies with large file chunking.
- Agentic RAG intelligently orchestrates context gathering for AI suggestions.
- Central agent_query tool plans multi-step tasks using internal capabilities.
- Supports local LLMs via Ollama or cloud AI like DeepSeek.
- Extensive environment variable configuration for indexing and agent behavior.
Use cases of CodeCompass
- Analyze a large legacy codebase to understand its structure and dependencies.
- Get AI-powered code suggestions for modifying or extending existing code.
- Perform semantic code search across a repository with natural language queries.
- Switch between local and cloud AI models depending on privacy or performance needs.
Frequently asked questions
How do I set up CodeCompass with a cloud AI provider?
Set the environment variable `LLM_PROVIDER` to `"deepseek"` and provide your `DEEPSEEK_API_KEY`. You can set these in your shell, a `.env` file, or through your MCP client’s configuration.
How can I switch the suggestion model at runtime?
Use the `switch_suggestion_model` tool with parameters like `{"model": "deepseek-coder", "provider": "deepseek"}` via the CLI client or through an MCP client that supports tool calls.
What is the utility HTTP server for?
The utility HTTP server (default port 3001) provides health checks, indexing status, and repository update notifications. If the port is already in use by another CodeCompass instance, the new instance disables its own HTTP server and relays requests to the existing one.
How do I run CodeCompass as a client to execute specific tools?
Use `codecompass <tool_name> [json_parameters] [--repo <path>] [--json] [--port <number>]`. For example, `codecompass search_code '{"query": "database connection setup"}'` performs a semantic search and returns results.
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