mcpserver — agent-tools.cloud directory + MCP discovery
MCP serverAI & modelsThis integration connects your AI to the agent-tools.cloud directory, a catalog of x402 services and A2A agents. Once added, your AI can search that catalog by describing what it needs and get back matching services and agents for the task at hand.
Use mcpserver — agent-tools.cloud directory + MCP discovery in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add mcpserver — agent-tools.cloud directory + MCP discovery and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use mcpserver to search
No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.
Details
Available today. Use it from your connected AI after setup.
No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.
After adding it, tell your AI what you want to accomplish and ask it to look up matching services or agents in the directory.
What your AI can do with it
- Search the agent-tools.cloud directory by describing a need or intent
- Find x402 services that match a given task
- Discover A2A agents suited to a described job
- Surface matching options from the directory without manual browsing
Install mcpserver — agent-tools.cloud directory + MCP discovery
The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.
Claude Code
claude mcp add --transport http --scope user mcpserver-agent-tools-cloud-dire 'https://agent-tools.cloud/mcp-discovery/'Run it once in your project, then open /mcp to approve any sign-in the server asks for.
Claude Desktop
https://agent-tools.cloud/mcp-discovery/Add a custom connector in Settings, paste this address, and approve the sign-in.
Cursor
cursor://anysphere.cursor-deeplink/mcp/install?name=mcpserver-agent-tools-cloud-dire&config=eyJ1cmwiOiJodHRwczovL2FnZW50LXRvb2xzLmNsb3VkL21jcC1kaXNjb3ZlcnkvIn0=Open the link and Cursor adds the server at that address.
ChatGPT
https://agent-tools.cloud/mcp-discovery/In Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.
Codex
codex mcp add mcpserver-agent-tools-cloud-dire --url 'https://agent-tools.cloud/mcp-discovery/'Run it once, then sign in with codex mcp login mcpserver-agent-tools-cloud-dire if the server asks for an account.
From the project's README
As published by agenttools-cloud/agenttoolscollection in README.md.
The server that powers agent-tools.cloud — an open directory of x402 paid services with a free MCP discovery endpoint. Also listed on Smithery.
Note (2026-05-25): the previously hosted paid Qwen3.6 relay and the paid vertical endpoints (signal / onchain / defi / portfolio) were retired after 30 days of zero external conversions. This repository now serves the directory site and the free MCP discovery server only.
What this serves today
| Path | Auth | Purpose |
|---|---|---|
GET / (host = agent-tools.cloud) | free | Directory site (search / browse) |
GET /api/v1/search | free | Faceted service search |
POST /api/v1/ask | free, rate-limited | LLM-ranked recommendations grounded in directory candidates |
GET /api/v1/services/{slug} | free | Service card with payment, call and quality metadata |
GET /api/v1/categories, /api/v1/stats | free | Directory facets and aggregate stats |
POST /api/v1/submit | free, rate-limited | Pending service submission with dedupe |
POST /mcp-discovery/ | free | MCP streamable-http discovery server |
POST /a2a | free | A2A JSON-RPC agent (message/send): directory search + MCP safety scan |
GET /healthz | free | Liveness |
GET /v1/models | free | Upstream model listing (read-only) |
GET /.well-known/agent-tools.json | free | Agent discovery manifest |
GET /.well-known/x402 | free | x402 v0.4 self-description (free-only) |
GET /.well-known/mcp.json | free | MCP self-description |
The MCP discovery server is also published as a standalone PyPI package:
agent-tools-mcp
(repo).
MCP discovery tools
search(intent, top_k=5, category=None, max_price_usd=None, has_mcp=None)
ask_services(intent, top_k=5, category=None, max_price_usd=None, use_llm=True)
get(slug)
list_categories()
stats()
search_mcp_servers(intent, top_k=5, chain=None, require_healthy=False)
get_mcp_server(slug)
search_a2a_agents(intent, top_k=5, x402_only=False)
search_resources(intent, protocol=None, top_k=10)
scan_mcp_safety(endpoint_url, name="", description="", tools_text="")
register(url, name=None, description=None, mcp_url=None, category=None)
search accepts natural-language intent and ranks by FTS5 + popularity +
health. Each result carries a match_reason and a confidence score.
ask_services uses the same retrieval-first / LLM-rerank flow as /api/v1/ask.
scan_mcp_safety vets an MCP server (by endpoint URL) for malware /
prompt-injection lures before you connect: an already-indexed server returns our
latest stored verdict, an unknown one is probed live, scanned, and added to the
directory. The verdict comes from deterministic static rules (no code execution)
over the server's advertised name + description + tool docs. Rules cover
pipe-to-shell / base64-eval / PowerShell install cradles, bare-IP payload hosts,
prompt-injection phrasing, and MCP tool-poisoning coercion — "always call
this tool first", "before using any other tool you must…", hidden
<IMPORTANT> instructions, "list all API keys / include secrets in your
response", and coercion to read & forward .key/.pem/.ssh/.env files.
Source-code-oriented rules (SQL/command/code injection) are intentionally not
applied to natural-language descriptions to avoid false positives. Each live
call also runs a frontier-LLM second opinion as an advisory dimension.
It is also exposed as an A2A skill on POST /a2a. The hosted server carries the
full tool set above; the stdio agent-tools-mcp PyPI package ships the core
search tools only.
Deploy
Currently deployed on latex-tools behind nginx (vhost: agent-tools.cloud).
cd /opt/mcpserver
sudo git pull
sudo systemctl restart mcpserver
systemd units live in deploy/:
mcpserver.service— the ASGI app (uvicorn, 127.0.0.1:9100)agent-tools-crawl.{service,timer}— 6h directory crawleragent-tools-health.{service,timer}— endpoint health checks
Config
See .env.example. Required:
UPSTREAM_BASE_URL/UPSTREAM_API_KEY— used by/v1/modelsAGENT_TOOLS_ASK_BASE_URL/AGENT_TOOLS_ASK_API_KEY/AGENT_TOOLS_ASK_MODEL— LLM backend for/api/v1/askAGENT_TOOLS_SAFETY_BASE_URL/AGENT_TOOLS_SAFETY_API_KEY/AGENT_TOOLS_SAFETY_MODEL— optional override for thescan_mcp_safetyadvisory LLM (falls back to theAGENT_TOOLS_ASK_*backend)AGENT_TOOLS_DB_PATH— SQLite path for the directoryAGENT_TOOLS_ASK_RATE_LIMIT_PER_MINUTE/AGENT_TOOLS_ASK_RATE_LIMIT_PER_DAY— public ask abuse limitsMETRICS_BEARER_TOKEN— optional remote access token for/metrics; without it metrics are local-only
Smoke test
# Liveness
curl https://agent-tools.cloud/healthz
# Directory stats
curl https://agent-tools.cloud/api/v1/stats
# Intent-level service recommendation
curl -s -X POST https://agent-tools.cloud/api/v1/ask \
-H 'content-type: application/json' \
-d '{"query":"find a weather API that accepts x402","limit":2}'
# Service card
curl https://agent-tools.cloud/api/v1/services/weather-hugen-tokyo-scan
# MCP discovery handshake
curl -s -X POST https://agent-tools.cloud/mcp-discovery/ \
-H 'content-type: application/json' \
-H 'accept: application/json, text/event-stream' \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize",
"params":{"protocolVersion":"2025-06-18","capabilities":{},
"clientInfo":{"name":"smoke","version":"1"}}}'
# Retired paid path -> 404
curl -s -o /dev/null -w '%{http_code}\n' -X POST \
https://agent-tools.cloud/v1/chat/completions \
-H 'content-type: application/json' \
-d '{"model":"Qwen/Qwen3.6-35B-A3B","messages":[{"role":"user","content":"hi"}]}'
# => 404
License
The agent-tools.cloud server and directory code in this repository is licensed under the PolyForm Noncommercial License 1.0.0 — you may use, modify, and share it for any noncommercial purpose; commercial use is not permitted.
The standalone MCP client package in agent-tools-mcp/
(published to PyPI as agent-tools-mcp) is licensed separately under
Apache-2.0, so any agent — including commercial
ones — can install and call the hosted service freely.
Using the hosted service at agent-tools.cloud is governed by its terms of service, not this code license.
Tools it offers (11)
What this server listed when Ahel dialed its public endpoint in Oct 2026, with no key and no account of yours. The names are the server’s own.
searchask_servicesgetlist_categoriesstatssearch_mcp_serversget_mcp_serversearch_a2a_agentssearch_resourcesregisterscan_mcp_safety
Signals
- GitHub stars
- 1
- Forks
- 1
- Last commit
- Oct 2026
Advanced
- Delivery
- agent-tools-mcp MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
- Item type
- mcp-server
- Key
io-github-agenttools-cloud-agent-tools-mcp- Source
- github.com/agenttools-cloud/agenttoolscollection
- Hosted endpoint
https://agent-tools.cloud/mcp-discovery/
github.com/agenttools-cloud/agenttoolscollection
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