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

| Tool | Description |

| ---------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |

| get_context_tree | Structural AST tree of a project with file headers and symbol ranges (line numbers for functions/classes/methods). Dynamic pruning shrinks output automatically. |

| get_file_skeleton | Function signatures, class methods, and type definitions with line ranges, without reading full bodies. Shows the API surface. |

| semantic_code_search | Search by meaning, not exact text. Uses embeddings over file headers/symbols and returns matched symbol definition lines. |

| semantic_identifier_search | Identifier-level semantic retrieval for functions/classes/variables with ranked call sites and line numbers. |

| semantic_navigate | Browse codebase by meaning using spectral clustering. Groups semantically related files into labeled clusters. |

Analysis

| Tool | Description |

| --------------------- | ----------------------------------------------------------------------------------------------------------------------------- |

| get_blast_radius | Trace every file and line where a symbol is imported or used. Prevents orphaned references. |

| run_static_analysis | Run native linters and compilers to find unused variables, dead code, and type errors. Supports TypeScript, Python, Rust, Go. |

Code Ops

| Tool | Description |

| ----------------- | ------------------------------------------------------------------------------------------------------------------------ |

| propose_commit | The only way to write code. Validates against strict rules before saving. Creates a shadow restore point before writing. |

| get_feature_hub | Obsidian-style feature hub navigator. Hubs are .md files with [[wikilinks]] that map features to code files. |

Version Control

| Tool | Description |

| --------------------- | ---------------------------------------------------------------------------------------------------------- |

| list_restore_points | List all shadow restore points created by propose_commit. Each captures file state before AI changes. |

| undo_change | Restore files to their state before a specific AI change. Uses shadow restore points. Does not affect git. |

Memory & RAG

| Tool | Description |

| ------------------------- | -------------------------------------------------------------------------------------------------------- |

| upsert_memory_node | Create or update a memory node (concept, file, symbol, note) with auto-generated embeddings. |

| create_relation | Create typed edges between nodes (relatesto, dependson, implements, references, similar_to, contains). |

| search_memory_graph | Semantic search with graph traversal — finds direct matches then walks 1st/2nd-degree neighbors. |

| prune_stale_links | Remove decayed edges (e^(-λt) below threshold) and orphan nodes with low access counts. |

| add_interlinked_context | Bulk-add nodes with auto-similarity linking (cosine ≥ 0.72 creates edges automatically). |

| retrieve_with_traversal | Start from a node and walk outward — returns all reachable neighbors scored by decay and depth. |

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:

| IDE | Config File |

| ----------- | -------------------- |

| Claude Code | .mcp.json |

| Cursor | .cursor/mcp.json |

| VS Code | .vscode/mcp.json |

| Windsurf | .windsurf/mcp.json |

| OpenCode | opencode.json |

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).

Including paths excluded by the workspace .gitignore

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.

From Source

npm install
npm run build

Embedding Providers

Context+ supports two embedding backends controlled by CONTEXTPLUS_EMBED_PROVIDER:

| Provider | Value | Requires | Best For |

|----------|-------|----------|----------|

| Ollama (default) | ollama | Local Ollama server | Free, offline, private |

| OpenAI-compatible | openai | API key | Gemini (free tier), OpenAI, Groq, vLLM |

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 refreshes changed files/functions incrementally.

Config

| Variable | Type | Default | Description |

| --------------------------------------- | ------------------------- | -------------------------------------- | ------------------------------------------------------------- |

| CONTEXTPLUS_EMBED_PROVIDER | string | ollama | Embedding backend: ollama or openai |

| OLLAMA_EMBED_MODEL | string | nomic-embed-text | Ollama embedding model |

| OLLAMA_API_KEY | string | - | Ollama Cloud API key |

| OLLAMA_CHAT_MODEL | string | llama3.2 | Ollama chat model for cluster labeling |

| CONTEXTPLUS_OPENAI_API_KEY | string | - | API key for OpenAI-compatible provider (alias: OPENAI_API_KEY) |

| CONTEXTPLUS_OPENAI_BASE_URL | string | https://api.openai.com/v1 | OpenAI-compatible endpoint URL (alias: OPENAI_BASE_URL) |

| CONTEXTPLUS_OPENAI_EMBED_MODEL | string | text-embedding-3-small | OpenAI-compatible embedding model (alias: OPENAI_EMBED_MODEL) |

| CONTEXTPLUS_OPENAI_CHAT_MODEL | string | gpt-4o-mini | OpenAI-compatible chat model for labeling (alias: OPENAI_CHAT_MODEL) |

| CONTEXTPLUS_EMBED_BATCH_SIZE | string (parsed as number) | 8 | Embedding batch size per GPU call, clamped to 5-10 |

| CONTEXTPLUS_EMBED_CHUNK_CHARS | string (parsed as number) | 2000 | Per-chunk chars before merge, clamped to 256-8000 |

| CONTEXTPLUS_MAX_EMBED_FILE_SIZE | string (parsed as number) | 51200 | Skip non-code text files larger than this many bytes |

| CONTEXTPLUS_EMBED_NUM_GPU | string (parsed as number) | - | Optional Ollama embed runtime num_gpu override |

| CONTEXTPLUS_EMBED_MAIN_GPU | string (parsed as number) | - | Optional Ollama embed runtime main_gpu override |

| CONTEXTPLUS_EMBED_NUM_THREAD | string (parsed as number) | - | Optional Ollama embed runtime num_thread override |

| CONTEXTPLUS_EMBED_NUM_BATCH | string (parsed as number) | - | Optional Ollama embed runtime num_batch override |

| CONTEXTPLUS_EMBED_NUM_CTX | string (parsed as number) | - | Optional Ollama embed runtime num_ctx override |

| CONTEXTPLUS_EMBED_LOW_VRAM | string (parsed as boolean)| - | Optional Ollama embed runtime low_vram override |

| CONTEXTPLUS_EMBED_TRACKER | string (parsed as boolean)| true | Enable realtime embedding refresh on file changes |

| CONTEXTPLUS_EMBED_TRACKER_MAX_FILES | string (parsed as number) | 8 | Max changed files processed per tracker tick, clamped to 5-10 |

| CONTEXTPLUS_EMBED_TRACKER_DEBOUNCE_MS | string (parsed as number) | 700 | Debounce window before tracker refresh |

Test

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