Space Frontiers

Space Frontiers API के साथ इंटरफेस करता है, जिससे भाषा मॉडल इसके डेटा स्रोतों के साथ बातचीत कर सकते हैं।

दस्तावेज़

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), machinelibrary_search_feedback, machinelibrary_comment_on_document, and machinelibrary_top_up_balance (purchases prepaid credits; not read-only); 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 \
SPACE_FRONTIERS_API_KEY=sf_live_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 — spacefrontiers://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. The hosted server still accepts legacy spacefrontiers_* tool calls and the former https://mcp.spacefrontiers.org endpoint; new setups should use the machinelibrary names and https://mcp.machinelibrary.ai.

License

MIT