ICML Paper Search MCP
MCP server for searching ICML 2026 papers with hybrid retrieval (dense + BM25), session management to avoid duplicates, and persistent state.
README
ICML Paper Search MCP
English | 简体中文 | Documentation
An open-source MCP service for searching 6,341 ICML 2026 papers. It provides six tools for search, paper lookup, corpus metadata, and search sessions. Within a session, papers already returned are not returned again.
Add the public MCP
Claude Code:
claude mcp add --transport http icml-papers --scope user \
https://icml.agent4sci.com:20441/mcp
Generic Streamable HTTP configuration:
{
"mcpServers": {
"icml-papers": {
"type": "http",
"url": "https://icml.agent4sci.com:20441/mcp"
}
}
}
The public instance is free to use while its shared quota is available.
Tools
| Tool | Purpose |
|---|---|
open_search_session |
Start a session |
search_papers |
Search papers and optionally deduplicate within a session |
search_session_status |
Read session status |
close_search_session |
Close a session |
get_papers |
Fetch papers by OpenReview ID |
list_paper_areas |
List research areas and paper types |
Self-host with Docker
Requirements: Docker Compose and a DashScope key with access to qwen3.7-text-embedding.
mkdir -p deploy/secrets
printf '%s' 'YOUR_DASHSCOPE_KEY' > deploy/secrets/dashscope_api_key
chmod 600 deploy/secrets/dashscope_api_key
docker compose -f deploy/compose.yaml -f deploy/milvus.compose.yaml \
up -d etcd minio standalone
docker compose -f deploy/compose.yaml -f deploy/milvus.compose.yaml \
--profile build run --rm build-index
docker compose -f deploy/compose.yaml -f deploy/milvus.compose.yaml \
up -d icml-mcp
The local MCP endpoint is http://127.0.0.1:20442/mcp. The Compose files include Milvus Standalone, etcd, and MinIO. Index data and runtime state are stored in Docker volumes.
See Local deployment for direct Python setup and configuration.
Retrieval
Milvus runs dense COSINE search and native BM25 search over each query, then combines the two rankings with standard RRF. DashScope supplies the query and document embeddings. SQLite stores session state, request limits, and the embedding cache.
Direction
The long-term work is to make retrieval more robust and add open scholarly data sources whose licensing and metadata quality can be verified.
Development
uv sync
uv run python -m pytest
License
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