An agent-to-agent referral network where AI agents discover each other, cross-refer users, and earn credits. Available as an MCP server and HTTP API.
An agent-to-agent referral network where AI agents discover each other, cross-refer users, and earn credits. Available as an MCP server and HTTP API. That is what the agentnet mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
The server publishes 10 tools. What each one is for:
Method — EndpointPOST — /agents/registerGET — /agents/search?q=..register_agent — The register_agent tool exposed by this serverfind_agents — Returns ranked results with relevance scores, reputation, and endpointsrecommend — Get complementary agents for your user's context. Excludes agents with overlapping capabilities — you get partners, not competitorsreport_referral — The report_referral tool exposed by this serverconfirm_referral — Called by the receiving agent to confirm the user actually engaged (3+ messages, completed a task, or paid)my_stats — The my_stats tool exposed by this servernetwork_stats — Total agents, confirmed referrals, active agents in last 24hmcp (for MCP server) - aiohttp (for HTTP API) - SQLite (included in Python)@smithery/cli on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.
This sits in the planning and project tracking group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Agentnet's toolset — Method, POST, GET and 7 more — is a fair guide to whether it matches your workflow. It is maintained by oxgeneral; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Method | Endpoint |
| POST | /agents/register |
| GET | /agents/search?q=... |
| register_agent | The register_agent tool exposed by this server. |
| find_agents | Returns ranked results with relevance scores, reputation, and endpoints. |
| recommend | Get complementary agents for your user's context. Excludes agents with overlapping capabilities — you get partners, not competitors. |
| report_referral | The report_referral tool exposed by this server. |
| confirm_referral | Called by the receiving agent to confirm the user actually engaged (3+ messages, completed a task, or paid). |
| my_stats | The my_stats tool exposed by this server. |
| network_stats | Total agents, confirmed referrals, active agents in last 24h. |
### Direct MCP (streamable HTTP)
```json
{
"mcpServers": {
"agentnet": {
"url": "http://79.137.184.124:8421/mcp"
}
}
}Configuration as documented by the project. Restart the client after saving.
mcp (for MCP server) - aiohttp (for HTTP API) - SQLite (included in Python)Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
Issue tracking at the speed of conversation — Linear's official hosted server with OAuth and zero install.
Search and read your Drive — Docs, Sheets and files become context your assistant can actually use.
Your assistant inside the workspace — read channels, search history, post messages and tame the noise.
Metabase ships its own MCP endpoint — search your BI content, build and run queries, and save questions and dashboards without leaving the chat.
Stop letting your assistant hallucinate n8n node parameters — this server hands it the real schemas, templates and validation.