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.

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.

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:

• 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).

If your workspace .gitignore excludes a sub-directory that you still want indexed (common in monorepos where sub-projects under repos/, packages/, or vendor/ are gitignored at the top level), use --include or CONTEXTPLUS_EXTRA_ROOTS to add the paths back.

CLI form (repeatable):

bunx contextplus /path/to/workspace \
  --include repos/lacuna \
  --include repos/graphrag-core

Environment variable (fallback when no --include flag is set; uses the system path separator — : on Unix, ; on Windows):

CONTEXTPLUS_EXTRA_ROOTS=repos/lacuna:repos/graphrag-core \
  bunx contextplus /path/to/workspace

In .mcp.json the env form is usually more ergonomic:

{
  "mcpServers": {
    "contextplus": {
      "command": "bunx",
      "args": ["contextplus", "/path/to/workspace"],
      "env": {
        "CONTEXTPLUS_EXTRA_ROOTS": "repos/lacuna:repos/graphrag-core"
      }
    }
  }
}

Each path listed is walked independently of the workspace root, with a fresh ignore scope. Each path's own .gitignore is respected. Paths are validated at startup; invalid entries (non-existent, not a directory, outside the workspace) emit a stderr warning and are skipped.

Nested .gitignore files inside the workspace and inside each extra root are loaded and merged with inherited rules, matching git and ripgrep behavior.

npm install
npm run build

Context+ supports two embedding backends controlled by CONTEXTPLUS_EMBED_PROVIDER:

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

ollama pull nomic-embed-text
ollama serve

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.

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

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).

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 refreshes changed files/functions incrementally.

npm test
npm run test:demo
npm run test:all