Context+

Semantic Intelligence for Large-Scale Engineering.

Context+ is an MCP server designed for developers who demand 99% accuracy. By combining RAG, Tree-sitter AST, Spectral Clustering, and Obsidian-style linking, Context+ turns a massive codebase into a searchable, hierarchical feature graph.

https://github.com/user-attachments/assets/a97a451f-c9b4-468d-b036-15b65fc13e79

Tools

Discovery

Analysis

Code Ops

Version Control

Memory & RAG

Complementary server: pmll-memory-mcp (npx pmll-memory-mcp) is a separate MCP server by @drQedwards that adapts Context+'s long-term memory graph and adds short-term KV context memory, Q-promise deduplication, and a solution engine on top. See drQedwards/PPM for details.

Setup

Quick Start (npx / bunx)

No installation needed. Add Context+ to your IDE MCP config.

For Claude Code, Cursor, and Windsurf, use mcpServers:

{
  "mcpServers": {
    "contextplus": {
      "command": "bunx",
      "args": ["contextplus"],
      "env": {
        "OLLAMA_EMBED_MODEL": "nomic-embed-text",
        "OLLAMA_CHAT_MODEL": "gemma2:27b",
        "OLLAMA_API_KEY": "YOUR_OLLAMA_API_KEY"
      }
    }
  }
}

For VS Code (.vscode/mcp.json), use servers and inputs:

{
  "servers": {
    "contextplus": {
      "type": "stdio",
      "command": "bunx",
      "args": ["contextplus"],
      "env": {
        "OLLAMA_EMBED_MODEL": "nomic-embed-text",
        "OLLAMA_CHAT_MODEL": "gemma2:27b",
        "OLLAMA_API_KEY": "YOUR_OLLAMA_API_KEY"
      }
    }
  },
  "inputs": []
}

If you prefer npx, use:

• "command": "npx"
• "args": ["-y", "contextplus"]

Or generate the MCP config file directly in your current directory:

npx -y contextplus init claude
bunx contextplus init cursor
npx -y contextplus init opencode

Supported coding agent names: claude, cursor, vscode, windsurf, opencode.

Config file locations:

CLI Subcommands

• init [target] - Generate MCP configuration (targets: claude, cursor, vscode, windsurf, opencode).
• skeleton [path] or tree [path] - (New) View the structural tree of a project with file headers and symbol definitions directly in your terminal.
• [path] - Start the MCP server (stdio) for the specified path (defaults to current directory).

From Source

npm install
npm run build

Embedding Providers

Context+ supports two embedding backends controlled by CONTEXTPLUS_EMBED_PROVIDER:

Ollama (Default)

No extra configuration needed. Just run Ollama with an embedding model:

ollama pull nomic-embed-text
ollama serve

Google Gemini (Free Tier)

Full Claude Code .mcp.json example:

{
  "mcpServers": {
    "contextplus": {
      "command": "npx",
      "args": ["-y", "contextplus"],
      "env": {
        "CONTEXTPLUS_EMBED_PROVIDER": "openai",
        "CONTEXTPLUS_OPENAI_API_KEY": "YOUR_GEMINI_API_KEY",
        "CONTEXTPLUS_OPENAI_BASE_URL": "https://generativelanguage.googleapis.com/v1beta/openai",
        "CONTEXTPLUS_OPENAI_EMBED_MODEL": "text-embedding-004"
      }
    }
  }
}

Get a free API key at Google AI Studio.

OpenAI

{
  "mcpServers": {
    "contextplus": {
      "command": "npx",
      "args": ["-y", "contextplus"],
      "env": {
        "CONTEXTPLUS_EMBED_PROVIDER": "openai",
        "OPENAI_API_KEY": "sk-...",
        "OPENAI_EMBED_MODEL": "text-embedding-3-small"
      }
    }
  }
}

Other OpenAI-compatible APIs (Groq, vLLM, LiteLLM)

Any endpoint implementing the OpenAI Embeddings API works:

{
  "mcpServers": {
    "contextplus": {
      "command": "npx",
      "args": ["-y", "contextplus"],
      "env": {
        "CONTEXTPLUS_EMBED_PROVIDER": "openai",
        "CONTEXTPLUS_OPENAI_API_KEY": "YOUR_KEY",
        "CONTEXTPLUS_OPENAI_BASE_URL": "https://your-proxy.example.com/v1",
        "CONTEXTPLUS_OPENAI_EMBED_MODEL": "your-model-name"
      }
    }
  }
}

Note: The semantic_navigate tool also uses a chat model for cluster labeling. When using the openai provider, set CONTEXTPLUS_OPENAI_CHAT_MODEL (default: gpt-4o-mini).

For VS Code, Cursor, or OpenCode, use the same env block inside your IDE's MCP config format (see Config file locations table above).

Architecture

Three layers built with TypeScript over stdio using the Model Context Protocol SDK:

Core (src/core/) - Multi-language AST parsing (tree-sitter, 43 extensions), gitignore-aware traversal, Ollama vector embeddings with disk cache, wikilink hub graph, in-memory property graph with decay scoring.

Tools (src/tools/) - 17 MCP tools exposing structural, semantic, operational, and memory graph capabilities.

Git (src/git/) - Shadow restore point system for undo without touching git history.

Runtime Cache (.mcp_data/) - created on server startup; stores reusable file, identifier, and call-site embeddings to avoid repeated GPU/CPU embedding work. A realtime tracker refreshe