toolatlas-mcp 0.1.2

ToolAtlas — Discover, Govern, and Optimize MCP Tools

ToolAtlas-MCP

The Control Plane for Your MCP Tools

ToolAtlas sits between AI clients and MCP servers — giving you a central registry, intelligent proxy, per-tool governance, usage analytics, and a web dashboard.

pip install toolatlas-mcp
toolatlas start

---

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  │
│                 │     │  ┌──────────────┐  ┌─────────────┐ │     │  PagerDuty MCP   │
│                 │     │  │ Registry     │  │ Analytics   │ │     │  AWS 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.

---

Features

🗂️ 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)

Each proxy gets its own endpoint:

http://localhost:8080/proxy/dev/message/{session_id}
http://localhost:8080/proxy/pm/message/{session_id}

🛡️ 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

Example — same server, different proxy settings:

Proxy "dev":  ✓ search_code  ✓ create_repo  ✗ delete_repo  ✓ list_issues
Proxy "pm":   ✓ search_code  ✗ create_repo  ✗ delete_repo  ✓ list_issues (read-only)

🏷️ 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 Term	Link to a business concept with definition	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.

🌐 Web Dashboard

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

---

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-MCP starting on 127.0.0.1:8080
  Web UI: http://127.0.0.1:8080
  API:    http://127.0.0.1:8080/api/health

Open http://localhost:8080 in your browser to see the dashboard.

2. Add an MCP Server

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 Servers → Add 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

5. Configure Tools Per Proxy

In the web UI, go to a Proxy detail page → Tools 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

6. Enrich Tool Metadata

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 Term — link to a business term with definition

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

7. Connect Your AI Client

Configure your MCP client (Claude Desktop, Cursor, custom agent) to point to ToolAtlas:

Type:     SSE
URL:      http://localhost:8080/proxy/dev/message/{session_id}

Each message gets a unique session_id (UUID). The proxy uses it to track call sequences.

Example: Python client

import httpx
import uuid

session_id = str(uuid.uuid4())
proxy_url = f"http://localhost:8080/proxy/dev/message/{session_id}"

# List tools
resp = httpx.post(proxy_url, json={
    "jsonrpc": "2.0", "id": 1, "method": "list_tools"
})
print(resp.json())

# Call a tool
resp = httpx.post(proxy_url, json={
    "jsonrpc": "2.0", "id": 2, "method": "call_tool",
    "params": {"name": "search_code", "arguments": {"query": "auth"}}
})
print(resp.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 (default: 127.0.0.1:8080)
toolatlas start --port 9000 --host 0.0.0.0	Start on a different address
toolatlas start --reload	Start with auto-reload (development)
toolatlas server add <name>	Register a new MCP server
toolatlas server list	List all registered servers
toolatlas proxy add <slug>	Create a new proxy
toolatlas proxy list	List all proxies
toolatlas proxy link <slug> <server>	Link a server to a proxy

---

Configuration

Set via environment variables with TOOLATLAS_ prefix:

Variable	Default	Description
TOOLATLAS_HOST	127.0.0.1	Bind address
TOOLATLAS_PORT	8080	HTTP port
TOOLATLAS_DATABASE_URL	sqlite+aiosqlite:///toolatlas.db	Database connection
TOOLATLAS_LOG_LEVEL	INFO	Log level (DEBUG, INFO, WARNING, ERROR)

Example:

export TOOLATLAS_HOST=0.0.0.0
export TOOLATLAS_PORT=9000
export TOOLATLAS_LOG_LEVEL=DEBUG
toolatlas start

---

Client Examples

Python

import httpx, uuid

session_id = str(uuid.uuid4())
base = f"http://localhost:8080/proxy/dev/message/{session_id}"

# List available tools
tools = httpx.post(base, json={
    "jsonrpc": "2.0", "id": 1, "method": "list_tools"
}).json()
print(tools)

# Call a tool
result = httpx.post(base, json={
    "jsonrpc": "2.0", "id": 2, "method": "call_tool",
    "params": {"name": "search_code", "arguments": {"query": "auth"}}
}).json()
print(result)

curl

SESSION_ID=$(uuidgen)

# List tools
curl -s -X POST "http://localhost:8080/proxy/dev/message/$SESSION_ID" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"list_tools"}'

# Call a tool
curl -s -X POST "http://localhost:8080/proxy/dev/message/$SESSION_ID" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":2,"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