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retrieval-mcp

An MCP server for the Retrieval academic-paper API - semantic paper search, document matching, ACE journal memory, and index inventory. Self-contained: it talks to the backend over HTTP only (just mcp + httpx), so it installs anywhere with uvx / pip - no repo checkout, no GPU, no models.

By default it targets the compute box on the lab LAN (http://10.100.100.111:8000), which trusts LAN callers so no key is needed. Off-LAN, point RETRIEVAL_API_URL at the public gateway (https://retrieval.rnarket.com) and set RETRIEVAL_API_KEY (sk-...).

Tools

Every tool's full docstring (purpose + each argument with its default + an example) is what your LLM sees - call them by name. Summary:

Paper retrieval

Tool What it does
search_papers Semantic hybrid search over 95k+ top-venue CS papers (filters: venue, year, title_only)
search_within_paper Every matching passage inside one paper
match_document / match_paper Content-nearest papers to a passage / to a paper
list_conferences / corpus_stats Venue registry / corpus size

Journal work-memory (scoped to the current project by default)

Tool What it does
journal_record Record a work note (memory) or a file's current content (doc, latest-wins)
journal_search Search memory - keyword (FTS5, no embedding) or hybrid/dense/sparse
journal_recent List recent entries
journal_index_dir Batch-index a local dir's files into the journal (latest-wins per file)

Code KB (source stays local - only chunks are uploaded)

Tool What it does
index_code AST-chunk a repo locally (40+ languages) and index it, scoped to you
search_code Semantic code search with path:line citations
index_inventory Your indexed-file tree: user -> host -> project -> dir -> file

ACE playbook (accumulated, curated lessons per project)

Tool What it does
ace_context_aware / ace_playbook Retrieve relevant / list all curated bullets
ace_enhance_prompt / ace_smart_generate Attach playbook lessons to a prompt (no LLM call)
ace_smart_reflect Curate a transferable lesson into the playbook (grow-and-refine dedup)

Code KB language coverage

index_code chunks 40+ languages structurally via tree-sitter (chonkie CodeChunker): Python, TypeScript/TSX/JS/JSX (React), Java, Kotlin (incl. Jetpack Compose .kt/.kts), Swift, Go, Rust, C/C++, C#, Ruby, PHP, Lua, Scala, Dart, R, Julia, Elixir, Erlang, Haskell, OCaml, SQL, GraphQL, Protobuf, HTML, CSS/SCSS (Tailwind = CSS classes), Vue, Svelte, shell, PowerShell, Dockerfile, Terraform/HCL, CMake, YAML/JSON/TOML/XML, and more. Grammarless config/text files fall back to line-window chunks; docs (.md) and binaries are skipped (docs belong in the journal via journal_index_dir).

Install

Claude Code

# LAN (no key):
claude mcp add retrieval -- uvx --from retrieval-mcp==0.2.29 retrieval-mcp
# Off-LAN (public gateway + key):
claude mcp add retrieval \
  --env RETRIEVAL_API_URL=https://retrieval.rnarket.com \
  --env RETRIEVAL_API_KEY=sk-... \
  -- uvx --from retrieval-mcp==0.2.29 retrieval-mcp

Claude Desktop / any MCP client

claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\):

{
  "mcpServers": {
    "retrieval": {
      "command": "uvx",
      "args": ["--from", "retrieval-mcp==0.2.29", "retrieval-mcp"],
      "env": {
        "RETRIEVAL_API_URL": "https://retrieval.rnarket.com",
        "RETRIEVAL_API_KEY": "sk-..."
      }
    }
  }
}

No uv? pip install retrieval-mcp then use "command": "retrieval-mcp".

Config (env)

Var Default Notes
RETRIEVAL_API_URL http://10.100.100.111:8000 LAN compute box (no key). Off-LAN, set to https://retrieval.rnarket.com.
RETRIEVAL_API_KEY - sk-... key for the gateway (create under /auth/keys). Required off-LAN.
Journal/code scope current absolute directory path The client derives scope from the directory you run or pass to each tool, so projects do not leak into each other.

License

MIT

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