Unified Dynamic MCP Server

Single MCP server with progressive discovery for 96-160x token reduction

Consolidates code understanding (Codanna), documentation (Context7), browser automation (Playwright), memory (Claude-mem), and knowledge graph (Graphiti+LadybugDB) into one unified server.

✨ NEW: Graphiti knowledge graph now supports Google Gemini! Use free Gemini API with embedded LadybugDB (no Docker required).

Features

✨ Progressive Discovery - 3-step pattern reduces tokens from 10,000+ to 50-200 🔧 Dynamic Tool Loading - Lazy load capabilities only when needed 🎯 5 Integrated Capabilities - Code, docs, browser, memory, knowledge graph 🚀 Git Submodules - Auto-update with git submodule update --remote ⚡ Fast - Sub-10ms symbol lookup (Codanna), embedded LadybugDB (no Docker)

Quick Start

# 1. Clone with submodules
git clone --recursive https://github.com/yourusername/unified-mcp.git
cd unified-mcp

# 2. Install dependencies (using uv - recommended)
uv pip install -r requirements.txt

# 3. Install Claude-mem plugin (required for memory capability)
# In Claude Code terminal:
/plugin marketplace add thedotmack/claude-mem
/plugin install claude-mem
# Then restart Claude Code

# 4. Add to Claude Code (replace /path/to/unified-mcp with actual path)
claude mcp add --transport stdio \
  unified-mcp \
  -- uv --directory /absolute/path/to/unified-mcp run server.py

# 5. For Graphiti + Google Gemini support (optional)
claude mcp add --transport stdio unified-mcp \
  -e GRAPHITI_ENABLED=true \
  -e GRAPHITI_LLM_PROVIDER=google_ai \
  -e GRAPHITI_EMBEDDER_PROVIDER=google_ai \
  -e GOOGLE_API_KEY=your-gemini-api-key-here \
  -e GRAPHITI_LLM_MODEL=gemini-1.5-pro \
  -e GRAPHITI_EMBEDDER_MODEL=text-embedding-004 \
  -- uv --directory /absolute/path/to/unified-mcp run server.py

# 6. Restart Claude Code and verify
# Ask Claude: "What tools do you have available?"

Manual Testing (optional):

# Run tests
pytest tests/ -v

# Start server directly
uv run server.py

Progressive Discovery Pattern

Traditional approach: Load all 20 tools upfront = 10,000 tokens

Our approach:

1. Search (search_tools) → Find relevant tools → ~50 tokens
2. Describe (describe_tools) → Get full schemas → ~200 tokens/tool
3. Execute (execute_tool) → Run the tool → Variable

Result: 98% token reduction 🎉

Architecture

Unified MCP Server
├── Progressive Discovery Engine
├── Dynamic Tool Registry
├── 5 Capability Modules
│   ├── Codanna (code understanding)
│   ├── Context7 (documentation)
│   ├── Playwright (browser automation)
│   ├── Claude-mem (memory)
│   └── Graphiti+LadybugDB (knowledge graph)

Installation

Requirements

• Python 3.12+ (for LadybugDB)
• Rust/Cargo (for Codanna) - Install Rust
• Node.js 18+ (for Context7/Playwright) - Install Node
• Claude Code (for Claude-mem plugin) - Install Claude Code

Claude-Mem Setup (Memory Capability)

Important: Claude-mem is a separate MCP server that runs as a Claude Code plugin. It must be installed before the unified-mcp memory capability will work.

Installation Steps:

1. Install via Claude Code Plugin Marketplace:

   # In Claude Code terminal
   /plugin marketplace add thedotmack/claude-mem
   /plugin install claude-mem
   

2. Restart Claude Code - The plugin auto-starts the HTTP API on http://localhost:37777

3. Verify Installation:

   # Check the service is running
   curl http://localhost:37777
   
   # Or visit the web UI
   open http://localhost:37777
   

4. Troubleshooting:

   # Use the built-in troubleshooting skill
   /claude-mem:troubleshoot
   

What Gets Installed:

• HTTP API service on port 37777 (auto-managed by Bun)
• SQLite database at ~/.claude-mem/claude-mem.db
• Web UI for browsing stored memories
• 5 lifecycle hooks for automatic memory capture
• Vector search via Chroma for semantic queries

Architecture:

• The unified-mcp server connects to claude-mem's HTTP API
• No direct npm installation needed - plugin handles all dependencies
• Auto-starts when Claude Code is running
• Stores observations across sessions with semantic search

For more details, see the claude-mem documentation.

Install Dependencies

# Python dependencies
pip install -r requirements.txt

# Codanna (code understanding)
cargo install codanna --all-features

# Git submodules (for Context7 and Playwright only - claude-mem is a plugin)
git submodule update --init --recursive
cd capabilities/context7 && npm install
cd ../playwright-mcp && npm install
# Note: claude-mem is installed as a Claude Code plugin (see above), not via npm

Codanna Auto-Indexing:

The server automatically creates and manages Codanna indexes:

• ✅ Automatic indexing on first run (indexes src, lib, handlers, core directories)
• ✅ No manual setup required - just install Codanna and start the server
• 🔄 Optional file watching - enable watch_changes: true in config/catalog.yaml to auto-reindex on file changes

To customize auto-indexing, edit config/catalog.yaml:

code_understanding:
  auto_index: true  # Auto-create index if missing
  watch_changes: false  # Watch files and re-index (requires watchdog)
  index_dirs:  # Directories to index
    - src
    - lib
    - your-custom-dir

Usage

Start Server

python server.py

Server runs on stdio (MCP protocol).

Configure with Claude Code

Option 1: Using claude mcp add (Recommended)

Replace /absolute/path/to/unified-mcp with your actual installation path.

Basic Configuration (No Graphiti):

claude mcp add --transport stdio \
  unified-mcp \
  -- uv --directory /absolute/path/to/unified-mcp run server.py

With Graphiti + Google Gemini:

claude mcp add --transport stdio unified-mcp \
  -e GRAPHITI_ENABLED=true \
  -e GRAPHITI_LLM_PROVIDER=google_ai \
  -e GRAPHITI_EMBEDDER_PROVIDER=google_ai \
  -e GOOGLE_API_KEY=your-gemini-api-key-here \
  -e GRAPHITI_LLM_MODEL=gemini-1.5-pro \
  -e GRAPHITI_EMBEDDER_MODEL=text-embedding-004 \
  -- uv --directory /absolute/path/to/unified-mcp run server.py

With Graphiti + OpenAI:

claude mcp add --transport stdio unified-mcp \
  -e GRAPHITI_ENABLED=true \
  -e GRAPHITI_LLM_PROVIDER=openai \
  -e GRAPHITI_EMBEDDER_PROVIDER=openai \
  -e OPENAI_API_KEY=sk-your-openai-key-here \
  -e GRAPHITI_LLM_MODEL=gpt-4o \
  -e GRAPHITI_EMBEDDER_MODEL=text-embedding-3-small \
  -- uv --directory /absolute/path/to/unified-mcp run server.py

With Graphiti + Anthropic Claude + Voyage Embeddings:

claude mcp add --transport stdio unified-mcp \
  -e GRAPHITI_ENABLED=true \
  -e GRAPHITI_LLM_PROVIDER=anthropic \
  -e GRAPHITI_EMBEDDER_PROVIDER=voyage_ai \
  -e ANTHROPIC_API_KEY=sk-ant-your-key-here \
  -e VOYAGE_API_KEY=pa-your-voyage-key-here \
  -e GRAPHITI_LLM_MODEL=claude-3-5-sonnet-20241022 \
  -e GRAPHITI_EMBEDDER_MODEL=voyage-3 \
  -- uv --directory /absolute/path/to/unified-mcp run server.py

With Graphiti + Local Ollama (Free):

claude mcp add --transport stdio unified-mcp \
  -e GRAPHITI_ENABLED=true \
  -e GRAPHITI_LLM_PROVIDER=ollama \
  -e GRAPHITI_EMBEDDER_PROVIDER=ollama \
  -e OLLAMA_BASE_URL=http://localhost:11434 \
  -e GRAPHITI_LLM_MODEL=llama3.1 \
  -e GRAPHITI_EMBEDDER_MODEL=nomic-embed-text \
  -- uv --directory /absolute/path/to/unified-mcp run server.py

Full Configuration Example (All Options):

claude mcp add --transport stdio unified-mcp \
  -e CODANNA_INDEX_DIR=.codanna \
  -e CLAUDE_MEM_API_URL=http://localhost:37777 \
  -e GRAPHITI_ENABLED=true \
  -e GRAPHITI_LLM_PROVIDER=google_ai \
  -e GRAPHITI_EMBEDDER_PROVIDER=google_ai \
  -e GOOGLE_API_KEY=your-gemini-api-key-here \
  -e GRAPHITI_LLM_MODEL=gemini-1.5-pro \
  -e GRAPHITI_EMBEDDER_MODEL=text-embedding-004 \
  -e GRAPHITI_DB_PATH=.graphiti/ladybug.db \
  -- uv --directory /absolute/path/to/unified-mcp run server.py

Option 2: Manual Configuration

Add to your MCP settings file (~/.config/claude/mcp_settings.json):

{
  "mcpServers": {
    "unified-mcp": {
      "command": "uv",
      "args": [
        "--directory",
        "/absolute/path/to/unified-mcp",
        "run",
        "server.py"
      ],
      "env": {
        "CODANNA_INDEX_DIR": "${workspaceFolder}/.codanna",
        "CLAUDE_MEM_API_URL": "http://localhost:37777",
        "GRAPHITI_ENABLED": "true",
        "GOOGLE_API_KEY": "your-gemini-api-key-here"
      }
    }
  }
}

With Graphiti + Google Gemini (Full Configuration):

{
  "mcpServers": {
    "unified-mcp": {
      "command": "uv",
      "args": [
        "--directory",
        "/absolute/path/to/unified-mcp",
        "run",
        "server.py"
      ],
      "env": {
        "CODANNA_INDEX_DIR": "${workspaceFolder}/.codanna",
        "CLAUDE_MEM_API_URL": "http://localhost:37777",
        "GRAPHITI_ENABLED": "true",
        "GRAPHITI_LLM_PROVIDER": "google_ai",
        "GRAPHITI_EMBEDDER_PROVIDER": "google_ai",
        "GOOGLE_API_KEY": "your-gemini-api-key-here",
        "GRAPHITI_LLM_MODEL": "gemini-1.5-pro",
        "GRAPHITI_EMBEDDER_MODEL": "text-embedding-004"
      }
    }
  }
}

Environment Variables:

Variable	Required	Default	Description
CODANNA_INDEX_DIR	No	.codanna	Codanna index directory
CLAUDE_MEM_API_URL	No	http://localhost:37777	Claude-mem API endpoint
GRAPHITI_ENABLED	No	false	Enable Graphiti knowledge graph
GRAPHITI_LLM_PROVIDER	No	openai	LLM provider: openai, anthropic, azure_openai, ollama, google_ai
GRAPHITI_EMBEDDER_PROVIDER	No	openai	Embedder: openai, voyage_ai, azure_openai, ollama, google_ai
GRAPHITI_LLM_MODEL	No	(varies)	Model name (e.g., gemini-2.5-flash, gpt-4o, claude-3-5-sonnet-20241022)
GRAPHITI_EMBEDDER_MODEL	No	(varies)	Embedder model (e.g., text-embedding-004, text-embedding-3-small)
GRAPHITI_RERANKER_MODEL	No	gemini-2.5-flash-lite	Reranker model (Gemini only)
GOOGLE_API_KEY	If using Gemini	-	Google AI API key for Gemini
OPENAI_API_KEY	If using OpenAI	-	OpenAI API key
ANTHROPIC_API_KEY	If using Claude	-	Anthropic API key

Playwright Browser Configuration:

Browser automation runs with headless=false by default (shows browser window). Configure in config/catalog.yaml:

browser_automation:
  headless: false  # Set to true to run browser in background

Restart Claude Code to load the server.

Verify it's working:

• Ask Claude: "What tools do you have available?"
• You should see tools like search_tools, describe_tools, execute_tool, etc.

Configuration

Edit config/catalog.yaml:

capabilities:
  code_understanding:
    enabled: true  # Toggle capabilities
    tools: [search_code, get_call_graph, ...]

Tools Available

Progressive Discovery (Meta-tools):

• search_tools(query) - Find relevant tools
• describe_tools([names]) - Get full schemas
• execute_tool(name, args) - Run a tool

Capability Management:

• list_capabilities() - See all capabilities
• enable_capability(name) - Enable at runtime
• disable_capability(name) - Disable at runtime

Code Understanding (Codanna - Phase 2):

• search_code - Semantic code search
• get_call_graph - Function relationships
• find_symbol - Symbol lookup (sub-10ms)
• find_implementations - Find implementations

Documentation (Context7 - Phase 3):

• resolve_library_id - Resolve library name
• get_library_docs - Fetch documentation

Browser Automation (Playwright - Phase 3):

• playwright_navigate - Navigate to URL
• playwright_screenshot - Take screenshot
• playwright_click - Click element
• playwright_fill - Fill form field
• playwright_evaluate - Execute JavaScript

Memory (Claude-mem - Phase 4):

• mem_search - Search observations
• mem_get_observation - Get by ID
• mem_recent_context - Recent sessions
• mem_timeline - Timeline view

Knowledge Graph (Graphiti - Phase 4):

• store_insight - Store knowledge
• search_insights - Search insights
• query_graph - Cypher queries
• add_episode - Add episode

Development

Run Tests

# All tests
pytest tests/ -v

# Unit tests only
pytest tests/unit/ -v

# With coverage
pytest tests/ --cov=. --cov-report=term-missing

# Skip slow tests
pytest tests/ -m "not slow"

Project Structure

unified-mcp/
├── server.py              # Main MCP server
├── config/
│   └── catalog.yaml       # Capability configuration
├── core/
│   ├── dynamic_registry.py
│   ├── progressive_discovery.py
│   └── capability_loader.py
├── handlers/             # Capability handlers
├── capabilities/         # Git submodules
├── tests/               # Comprehensive test suite
└── docs/                # Documentation

Implementation Status

• ✅ Phase 1: Foundation (Dynamic registry, progressive discovery)
• ✅ Phase 2: Codanna integration (4 code understanding tools)
• ✅ Phase 3: Context7 + Playwright (7 tools: docs + browser automation)
• ✅ Phase 4: Claude-mem + Graphiti (8 tools: memory + knowledge graph)
• ✅ Phase 5: Comprehensive testing (Unit + Integration + E2E, 80%+ coverage, CI/CD)
• ✅ Phase 6: Documentation (Complete)

License

Apache 2.0

References

• MCP Specification
• Docker MCP Gateway
• Codanna
• Context7
• Playwright MCP
• Claude-mem