Space Frontiers MCP Server

Machine Library MCP Server

Official MCP server for Machine Library, the search and AI product by Space Frontiers Company.

• Endpoint: https://mcp.machinelibrary.ai (canonical)
• Server name: machinelibrary; tools are prefixed machinelibrary_
• Agent install guide: https://machinelibrary.ai/install.md

A retrieval layer for AI agents over peer-reviewed papers, books, patents, standards, Wikipedia, Reddit, Telegram, Discord, and YouTube. Returns bounded full text and canonical source URIs for citation.

Hosted at https://mcp.machinelibrary.ai/ (Streamable HTTP transport, OAuth 2.1 with PKCE or Bearer API key).

Try a worked example: Find research, inspect supporting passages, and retain citations. Includes exact tool calls and observations from a live run, plus a small evaluation checklist for research teams.

Tools

The four core retrieval tools below are read-only, idempotent, and prefixed machinelibrary_ to avoid collisions in multi-server agent setups. This repository implements them. The hosted server also exposes machinelibrary_research (cited research answers) and three write tools: machinelibrary_search_feedback, machinelibrary_comment_on_document and machinelibrary_vote_on_comment; see the tool guide or its tools/list.

Tool	When to use
machinelibrary_search_documents	Papers, books, patents, standards, Wikipedia, YouTube transcripts. Use for citations and prior art.
machinelibrary_search_social	Reddit, Telegram channels, Discord. Use for news and community discussion.
machinelibrary_fetch_document	Bounded full text + up to 50 references for one canonical URI. Defaults to 40K characters; supports up to 100K.
machinelibrary_search_in_document	Up to five matching passages within one document. Use for documents over ~20K tokens.

Search defaults to 10 compact, hybrid-ranked results and is capped at 30. Every hit includes a canonical source_uri, one snippet (up to 900 characters), an abstract preview (up to 800 characters), score, authors, date, type, and estimated full-text size. Citation backlinks are opt-in on machinelibrary_fetch_document because they add another billed search.

Install

The hosted server has its own /mcp install page with one-click links for Cursor, VS Code, and Smithery.

Claude Code (recommended)

claude mcp add --transport http --scope user machinelibrary https://mcp.machinelibrary.ai

On first use a browser opens for OAuth login — no API key paste required.

Cursor / VS Code / Cline / Windsurf (HTTP)

{
  "mcpServers": {
    "machinelibrary": {
      "type": "http",
      "url": "https://mcp.machinelibrary.ai",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

Get an API key at https://machinelibrary.ai/keys.

Self-hosted (stdio)

git clone https://github.com/SpaceFrontiers/mcp.git
cd mcp
uv sync
SEARCH_API_ENDPOINT=https://api.machinelibrary.ai \
MACHINELIBRARY_API_KEY=ml_xxx uv run fastmcp run mcp_server.py

The environment variable is used as the upstream API credential in stdio mode. The command selects the public Machine Library API with SEARCH_API_ENDPOINT. The internal default remains http://search-api for existing deployments. For HTTP deployments, set SEARCH_API_ENDPOINT to your trusted internal search API and USERS_API_ENDPOINT to your internal users API; the auth middleware forwards verified identity headers to that internal service. OAuth uses the https://api.machinelibrary.ai authorization server and browser sign-in at https://machinelibrary.ai.

Pricing

• Search: $0.01 base + $0.001 per returned result (the 10-result MCP default costs $0.02).
• Full document fetch: $0.05.
• In-document passage search: $0.015.
• referenced_by_limit > 0 on a fetch adds a separately billed search.

Add credits at https://machinelibrary.ai/payments.

Repository layout

• mcp_server.py — Starlette + FastMCP entrypoint, OAuth well-known endpoints.
• tools.py — four tools with Pydantic output schemas.
• prompts.py — deep_research_agent prompt.
• resources.py — machinelibrary://document/{uri_b64} URI template.
• auth.py — Bearer-token validation, Origin allowlist, MCP-Protocol-Version check.
• client.py — async HTTP client for the v2 search API.
• server.json — Official MCP Registry entry.
• smithery.yaml — Smithery deployment config.
• registry.json — in-house registry metadata.
• tests/ — pytest unit tests.

Spec compliance

• Transport: Streamable HTTP, stateless.
• Auth: OAuth 2.1 with RFC 7591 Dynamic Client Registration; long-lived API keys also accepted.
• Annotations: every tool declares readOnlyHint, idempotentHint, openWorldHint, destructiveHint:false.
• Output schemas: every tool's outputSchema is auto-generated from a Pydantic return model.
• Resources: one URI template registered for documents.
• Spec versions accepted: 2025-03-26, 2025-06-18, 2025-11-25.

Development

uv sync
uv run pytest
uv run ruff check .

mcp-name: io.github.SpaceFrontiers/mcp

Compatibility

Existing accounts and API keys work unchanged, and the former https://mcp.spacefrontiers.org endpoint remains supported; new setups should use https://mcp.machinelibrary.ai. The legacy spacefrontiers_* tool names were retired on 2026-10-07; use the machinelibrary_* names. Self-hosted servers still read SPACE_FRONTIERS_API_KEY when MACHINELIBRARY_API_KEY is unset.

License

MIT