openrouter-deep-research-mcp
by wheattoast11·★ 50·Score 47
Multi-agent research MCP server with async agents, semantic search, and persistent knowledge base.
Overview
OpenRouter Agents MCP Server is a production-ready platform that orchestrates a network of asynchronous AI agents to conduct consensus-backed research. It features an indexed PGlite database built in WebAssembly, hybrid search capabilities, SQL execution, and sophisticated agent communication protocols. The server supports both HTTP and STDIO transport modes and includes advanced features like embedding-based model routing, session management, and knowledge graph exploration.
Try asking AI
After installing, here are 5 things you can ask your AI assistant:
When to choose this
Choose this MCP server when you need sophisticated multi-agent research capabilities with persistent knowledge storage and advanced semantic search features.
When NOT to choose this
Don't choose this if you need a lightweight research tool without the complexity of multiple agents or if you prefer open-source models over commercial APIs.
Tools this server exposes
12 tools extracted from the READMEresearchAsync research that returns a job ID
conduct_researchSynchronous research with streaming results
batch_researchParallel batch queries for multiple research topics
searchHybrid BM25+vector search across the knowledge base
retrieveRetrieve data from index or perform SQL query
querySQL SELECT query with parameters
graph_traverseExplore the knowledge graph connections
graph_clustersFind node clusters in the knowledge graph
list_railsList rails, tunnels, routes, and consensus sessions
pingHealth check for the server
get_server_statusGet full server diagnostics and status
list_toolsList all available tools on the server
Comparable tools
Installation
Install with npm:
npx @terminals-tech/openrouter-agents --stdioFor Claude Desktop, add to config file:
{
"mcpServers": {
"openrouter-agents": {
"command": "npx",
"args": ["@terminals-tech/openrouter-agents"],
"env": {
"OPENROUTER_API_KEY": "sk-or-..."
}
}
}
}FAQ
- What models are supported?
- Supports both high-cost models (Claude, GPT-5, Gemini 3) and low-cost models (Gemini Flash, Claude Haiku) with embedding-based routing for optimal selection.
- How does the multi-agent research work?
- The system decomposes complex queries into sub-queries, assigns them to specialized agents, and synthesizes results through consensus-based protocols with proper citation.
Compare openrouter-deep-research-mcp with
Last updated · Auto-generated from public README + GitHub signals.