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ToolAtlas — Discover, Govern, and Optimize MCP Tools

Project description

ToolAtlas

The Knowledge Layer for MCP Tools

PyPI version Python License

Architecture

ToolAtlas helps organizations discover, govern, understand, and optimize MCP tools without modifying existing MCP servers.

pip install toolatlas-mcp
toolatlas start                  # defaults: port 8081, json storage
toolatlas start --port 9000 --storage sqlite --data-dir ./data

Why ToolAtlas?

As MCP adoption grows, teams quickly accumulate hundreds of tools across GitHub, Jira, Confluence, AWS, Databricks, Slack, internal systems, and custom MCP servers. The challenge is no longer connecting tools — it's understanding them.

Problem How ToolAtlas Solves It
Tool Sprawl Central catalog of every MCP tool — see what exists, what's used, what's duplicated, what's dangerous
Lack of Business Context Add business descriptions, aliases, tags, domain categories, and glossary definitions — without modifying the original server
Governance Per-proxy enable/disable, tool selection on server link, audit logging via call traces
Tool Intelligence Usage analytics, success rates, latency tracking, top tools by usage

ToolAtlas sits between AI clients and MCP servers — it's the control plane for your MCP ecosystem.

"LiteLLM manages models. ToolAtlas manages tools. "


Key Features

📋 MCP Tool Catalog

Central inventory of all MCP tools across all your servers — searchable, filterable, sortable from the web dashboard.

Dashboard

🗂️ Proxy Groups — Organize Tools by Team or Purpose

Create proxies (named groups) and assign MCP servers to each. Every proxy exposes a different toolset.

Proxy "dev"    → GitHub + GitLab     (for developers)
Proxy "pm"     → Jira + Confluence   (for project managers)
Proxy "devops" → AWS + PagerDuty     (for operations)

Proxy Configuration

🛡️ Per-Tool Governance — Control What Each Proxy Exposes

Every tool can be independently configured per proxy:

Control What it does
Enable / Disable Block dangerous tools (e.g. delete_repo) without touching the server
Custom Description Rewrite the tool's description so AI agents understand it in context
Alias Rename the tool per proxy
Tool Selection on Link Pick exactly which tools to expose when linking a server — unselected tools auto-disable

Tool Detail & Enrichment

🏷️ Tool Enrichment — Make Tools Smarter

Every registry tool can be enriched with business context. The enriched description is what clients see when they call list_tools:

Enrichment Purpose Example in client view
Custom Description Override the original server description Search for code in GitHub
Tags Add searchable labels Tags: git, code, search
Domain Categorize by business area Domain: development
Glossary Terms Link one or more business concepts with definitions Glossary: Search across all code repositories

Client sees the full enriched description automatically:

{
  "name": "search_code",
  "description": "Search code in GitHub repositories\nTags: git, code\nDomain: development\nGlossary: Search code across all repositories",
  "inputSchema": { ... }
}

📊 Usage Analytics

Every tool call is tracked — duration, success/failure, arguments. Dashboard shows top tools, latency trends, error rates, and per-call trace timelines.

Analytics

🌐 Web Dashboard

Full SPA for managing everything visually — servers, proxies, tool settings, glossary, analytics.

🧪 Tool Testing Console

Test any tool directly from the UI — pass arguments via a dynamic form (auto-generated from the tool's input schema) and see the result in real time with duration tracking.

📂 Glossary with Domain Hierarchy

Organize glossary terms under domains (created first, then terms under them). Terms are grouped by domain in the UI. Assign multiple glossary terms to a single tool. Edit/delete domains and terms inline. Bulk import entire glossaries via JSON/CSV file upload with automatic domain creation.

🔍 Filters & Search

Every management page (Tools, Servers, Proxies, Glossary, Analytics) includes search bars and filter dropdowns for quick navigation.

🔮 Planned Features

Feature Status
Tool Graph — Visualize relationships between tools and discover real execution workflows Planned
Tool Recommendations — Recommend the best tools for tasks based on usage patterns Planned

Architecture

┌─────────────────┐     ┌─────────────────────────────────────┐     ┌─────────────────┐
│  MCP Clients    │     │         ToolAtlas                    │     │  MCP Servers     │
│                 │     │                                     │     │                  │
│  Claude         │────▶│  Proxy "dev"     ── governance ──▶ │────▶│  GitHub MCP      │
│  Cursor         │────▶│  Proxy "pm"      ── governance ──▶ │────▶│  Jira MCP        │
│  Custom Agents  │────▶│  Proxy "devops"  ── governance ──▶ │────▶│  Slack MCP       │
│                 │     │                                     │     │  Confluence MCP  │
│                 │     │  ┌──────────────┐  ┌─────────────┐ │     │  AWS MCP         │
│                 │     │  │ Registry     │  │ Analytics   │ │     │  Custom MCP      │
│                 │     │  │ DB + API     │  │ Tracker     │ │     └─────────────────┘
│                 │     │  └──────────────┘  └─────────────┘ │
│                 │     │  ┌──────────────────────────────┐  │
│                 │     │  │  Web Dashboard (React SPA)   │  │
│                 │     │  └──────────────────────────────┘  │
│                 │     │  ┌──────────────────────────────┐  │
│                 │     │  │  CLI: toolatlas start/add    │  │
│                 │     │  └──────────────────────────────┘  │
│                 │     └─────────────────────────────────────┘

Clients speak MCP to ToolAtlas. ToolAtlas enforces governance, enriches tool descriptions, logs every call, and forwards to real MCP servers.


Installation

Prerequisites

  • Python 3.10+ (download)
  • pip (comes with Python)

Install from PyPI (recommended)

pip install toolatlas-mcp

Verify it installed:

toolatlas --help

You should see the CLI help with start, server, proxy commands.

Install from source

git clone https://github.com/anomalyco/toolatlas-mcp
cd toolatlas-mcp

# Python package
pip install -e ".[dev]"

# Build the web UI
cd ui
npm install
npm run build
cd ..

Usage — Step by Step

1. Start the Server

toolatlas start

Output:

ToolAtlas starting on 127.0.0.1:8081
  Web UI: http://127.0.0.1:8081
  API:    http://127.0.0.1:8081/api/health

Open http://localhost:8081 in your browser to see the dashboard.

2. Add an MCP Server

Server Management

You can add servers via CLI or the web UI.

CLI — stdio server (e.g., npx-based):

toolatlas server add github \
  --transport stdio \
  --command "npx" \
  --args "-y" "@modelcontextprotocol/server-github"

CLI — SSE server (already running):

toolatlas server add my-api \
  --transport sse \
  --url "http://localhost:9001/sse"

Web UI: Go to ServersAdd Server, fill in the details.

3. Discover Tools

After adding a server, discover its tools:

# Via CLI (uses the API):
curl -X POST http://localhost:8080/api/servers/{server_id}/discover

Or click Discover & Save New on the Server detail page in the web UI.

4. Create a Proxy

Proxies organize tools into groups. Each proxy exposes a subset of your servers' tools.

# Create a proxy
toolatlas proxy add dev --description "Developer tools"

# Link servers to it
toolatlas proxy link dev github
toolatlas proxy link dev gitlab

List your proxies:

toolatlas proxy list

Tip: In the web UI, when linking a server you can select exactly which tools to expose — unselected tools are automatically disabled for that proxy. No need to manually toggle them afterwards.

5. Configure Tools Per Proxy

In the web UI, go to a Proxy detail pageTools tab. For each tool:

  • Toggle enabled/disabled — disable delete_repo for the "dev" proxy
  • Set a custom description — e.g., "Search code in GitHub repos"
  • Alias the tool — rename it for clarity

You can also select which tools to include at link time — click Link next to a server to open the tool picker modal.

6. Enrich Tool Metadata

Tool Enrichment Settings

In the Tool detail page, you can add:

  • Tags — comma-separated labels like git, code, search
  • Domain — categorize the tool (e.g., "development", "security")
  • Glossary Terms — link one or more business terms with definitions (multi-select, grouped by domain)

First create glossary domains and terms under the Glossary page, then assign them to tools from the tool detail page.

7. Connect Your AI Client

Configure your MCP client (Claude Desktop, Cursor, custom agent) to point to ToolAtlas. Replace dev with your proxy's slug name.

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "dev": {
      "type": "sse",
      "url": "http://localhost:8081/proxy/dev/sse"
    }
  }
}

Cursor / VS Code / any MCP client — same format; just register an SSE server with the URL above.

The proxy slug (dev, prod, etc.) is the name you gave when creating the proxy. Each proxy exposes a different toolset.

Advanced: Raw JSON-RPC (without SSE)

For scripting or testing without an MCP client library, use the message endpoint directly. Each call needs its own session_id (UUID).

import httpx, uuid

session_id = str(uuid.uuid4())
proxy_url = f"http://localhost:8081/proxy/dev/message/{session_id}"

# Initialize
httpx.post(proxy_url, json={
    "jsonrpc": "2.0", "id": 1, "method": "initialize",
    "params": {"protocolVersion": "2024-11-05", "capabilities": {}, "clientInfo": {"name": "test", "version": "1.0"}}
}).json()

# Notify initialized
httpx.post(proxy_url, json={
    "jsonrpc": "2.0", "method": "notifications/initialized"
}).json()

# List tools
httpx.post(proxy_url, json={
    "jsonrpc": "2.0", "id": 2, "method": "list_tools"
}).json()

# Call a tool
httpx.post(proxy_url, json={
    "jsonrpc": "2.0", "id": 3, "method": "call_tool",
    "params": {"name": "search_code", "arguments": {"query": "auth"}}
}).json()

8. View Analytics

Go to the Analytics page in the web UI to see:

  • Total calls, success rate, average latency
  • Top tools by usage
  • Individual call traces with event timelines (proxy resolution → server call → response)

CLI Reference

Command Description
toolatlas start Start the ToolAtlas server (defaults: port 8081, json storage)
toolatlas start --port 9000 --host 0.0.0.0 Start on a different address
toolatlas start --storage sqlite Use SQLite storage backend
toolatlas start --data-dir ./my-data Custom data directory
toolatlas start --reload Start with auto-reload (development)

All flags: --port, --host, --storage (json/sqlite), --data-dir, --reload. Environment variables are still supported with TOOLATLAS_ prefix and take precedence over defaults.


Storage

ToolAtlas supports two storage backends:

Backend Type Best for
JSON File (default) json Development, single-user, portable setups, git-versioned data
SQLite sqlite Production, multi-user, analytics-heavy workloads

The data.json file is saved to the same data directory as the SQLite database.

Configuration

Set via environment variables with TOOLATLAS_ prefix:

Variable Default Description
TOOLATLAS_HOST 127.0.0.1 Bind address
TOOLATLAS_PORT 8081 HTTP port (auto-increments if in use)
TOOLATLAS_DATABASE_URL sqlite+aiosqlite:///<data_dir>/toolatlas.db Database connection (only for sqlite backend)
TOOLATLAS_STORAGE_TYPE json Storage backend (json or sqlite)
TOOLATLAS_DATA_DIR ~/.toolatlas (Unix) / %APPDATA%\ToolAtlas (Win) Data directory for databases and config
TOOLATLAS_LOG_LEVEL INFO Log level (DEBUG, INFO, WARNING, ERROR)
TOOLATLAS_BASE_PATH "" URL prefix when deployed behind a reverse proxy (e.g. /toolatlas)

When starting interactively, you'll be prompted for the data directory and storage type if the environment variables aren't set. The CLI automatically scans for a free port (8080→8280) if the default port is occupied.

Example:

export TOOLATLAS_HOST=0.0.0.0
export TOOLATLAS_PORT=9000
export TOOLATLAS_STORAGE_TYPE=json
export TOOLATLAS_DATA_DIR=./toolatlas-dev
toolatlas start

To use non-interactive mode (no prompts):

TOOLATLAS_DATA_DIR=/custom/path TOOLATLAS_STORAGE_TYPE=json toolatlas start

Subpath Deployment

To deploy ToolAtlas under a URL prefix (e.g. https://xyz.com/toolatlas/) behind a reverse proxy like Nginx:

  1. Set the base path:

    export TOOLATLAS_BASE_PATH=/toolatlas
    
  2. Rebuild the React UI with the subpath:

    cd ui
    VITE_BASE_URL=/toolatlas/ VITE_BASE_PATH=/toolatlas npm run build
    
  3. Configure Nginx to strip the /toolatlas prefix and proxy to ToolAtlas:

    location /toolatlas/ {
        proxy_pass http://127.0.0.1:8081/;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
        proxy_buffering off;
        proxy_read_timeout 86400s;
    }
    

The trailing slash in proxy_pass strips /toolatlas before forwarding, so ToolAtlas receives requests at /api/..., /proxy/... as usual. The base_path setting only affects URL generation (SSE message_url, OpenAPI docs).

  1. MCP clients connect to the full path:
    { "url": "https://xyz.com/toolatlas/proxy/dev/sse" }
    

See docs/deploy-under-subpath.md for full details.


Client Examples

Python

import httpx, uuid

session_id = str(uuid.uuid4())
base = f"http://localhost:8081/proxy/dev/message/{session_id}"

# Initialize (required before any other call)
httpx.post(base, json={
    "jsonrpc": "2.0", "id": 1, "method": "initialize",
    "params": {"protocolVersion": "2024-11-05", "capabilities": {}, "clientInfo": {"name": "test", "version": "1.0"}}
}).json()

httpx.post(base, json={"jsonrpc": "2.0", "method": "notifications/initialized"}).json()

# List available tools
tools = httpx.post(base, json={
    "jsonrpc": "2.0", "id": 2, "method": "list_tools"
}).json()
print(tools)

# Call a tool
result = httpx.post(base, json={
    "jsonrpc": "2.0", "id": 3, "method": "call_tool",
    "params": {"name": "search_code", "arguments": {"query": "auth"}}
}).json()
print(result)

curl

SESSION_ID=$(uuidgen)

# Initialize
curl -s -X POST "http://localhost:8081/proxy/dev/message/$SESSION_ID" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'

curl -s -X POST "http://localhost:8081/proxy/dev/message/$SESSION_ID" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","method":"notifications/initialized"}'

# List tools
curl -s -X POST "http://localhost:8081/proxy/dev/message/$SESSION_ID" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":2,"method":"list_tools"}'

# Call a tool
curl -s -X POST "http://localhost:8081/proxy/dev/message/$SESSION_ID" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":3,"method":"call_tool","params":{"name":"search_code","arguments":{"query":"auth"}}}'

Development

git clone https://github.com/anomalyco/toolatlas-mcp
cd toolatlas-mcp

# Python
pip install -e ".[dev]"

# UI
cd ui && npm install && npm run build && cd ..

# Tests
pytest

# Dev server (API only, UI served by Vite on port 5173)
toolatlas start --reload
# In another terminal:
cd ui && npm run dev

License

MIT © ToolAtlas contributors

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