Semantic Scholar MCP Server

A 14-tool Semantic Scholar MCP server for academic research workflows. Direct access to 200M+ papers from Semantic Scholar — paper search, citation graph traversal, author profiles, and recommendations — from any Model Context Protocol client (e.g., Claude Desktop, Claude Code, Cursor, Cline, Continue, and others).

Every release ships verifiable supply-chain provenance: Sigstore-signed SLSA build-provenance attestations on the wheel, sdist, and container image; PEP 740 attestations on the PyPI upload; and a CycloneDX SBOM — so you can prove the artifact you installed was built from this repo. See Provenance & supply chain.

Author: Santiago Maniches · ORCID 0009-0005-6480-1987 · TOPOLOGICA LLC

Quick start

uvx s2-mcp-server                                      # run instantly, no install
claude mcp add semantic-scholar -- uvx s2-mcp-server   # or register it in Claude Code

No API key is needed to start (public rate limit: 1 req/sec); set SEMANTIC_SCHOLAR_API_KEY for 10 req/sec. Claude Desktop, Docker, pip, and remote (Streamable HTTP) setups are in Installation.

Provenance & supply chain

A research tool is only as trustworthy as the chain from its source to the binary you run. Every release of this server ships cryptographically verifiable supply-chain evidence, all generated in CI from the tagged commit:

Guarantee	What it proves	Where it is produced
SLSA build provenance (wheel + sdist)	the published distributions were built by this repo's `publish.yml` from the released tag, not hand-uploaded	`publish.yml` — `actions/attest-build-provenance` (lines 56–59)
SLSA build provenance (container image)	the `ghcr.io` image digest was built by this repo's `docker.yml`	`docker.yml` — `actions/attest-build-provenance`, `push-to-registry` (lines 110–116)
PEP 740 attestations	the PyPI upload itself carries Sigstore-backed attestations under Trusted Publishing	`publish.yml` — `attestations: true` (line 97)
CycloneDX SBOM	a machine-readable bill of materials, generated then attested against the distributions	`publish.yml` — `cyclonedx-py` + `actions/attest-sbom` (lines 46–64)
SHA-pinned Actions	every CI action is pinned to a commit SHA, so the release pipeline itself cannot silently change	all jobs in `.github/workflows/` (e.g. `publish.yml`, `docker.yml`)

Verify the wheel and the container image against their attestations with the GitHub CLI:

# Wheel / sdist (download from the PyPI project or the release assets first)
gh attestation verify s2_mcp_server-*.whl --repo smaniches/semantic-scholar-mcp

# Container image
gh attestation verify oci://ghcr.io/smaniches/semantic-scholar-mcp:latest \
  --repo smaniches/semantic-scholar-mcp

The full supply-chain posture, including the known-limitations list, is in SECURITY.md. This is release-time provenance (proving how the artifact was built); the server does not currently attach a per-response receipt to individual API results.

How it compares

There is no public Semantic Scholar MCP standard, so the most useful comparison is against the obvious alternative: calling the Semantic Scholar REST API yourself from an agent. Everything in the right-hand column is plumbing this server already owns and the caller would otherwise reimplement.

	This server	Raw S2 REST API from an agent
Tool surface	14 typed MCP tools (search, retrieval, recommendations, status)	caller composes raw HTTP requests
Citation graph	both directions (citations and references) in `get_paper`	manual paging over two endpoints
Bulk operations	papers (≤500) and authors (≤1000) in one call	caller batches and paginates
Full-text snippet search	`snippet_search` with surrounding context	separate endpoint, caller-assembled
Paper-ID resolution	seven formats — Semantic Scholar ID, DOI, ArXiv, PubMed, Corpus ID, ACL, URL — validated pre-flight (`validators.py`)	caller normalizes and validates IDs
Rate limiting	client-side per-tier limiter, never exceeds the interval (`client.py`)	caller throttles by hand
Retry / backoff	bounded, jittered retry on 429/503/timeout, honors `Retry-After` (`client.py`)	caller implements retry
Errors	typed exception hierarchy, branchable by caller (`errors.py`)	parse HTTP status strings
Output	chat-tuned Markdown or JSON per call (`formatters.py`)	raw JSON
Supply-chain provenance	SLSA + PEP 740 + CycloneDX SBOM per release (see above)	n/a
Citability	minted Zenodo DOI, MIT licensed	n/a

Installation

Option 1: One-Line Install (Recommended)

# No cloning needed — runs directly from PyPI
uvx s2-mcp-server

Option 2: Claude Code

claude mcp add semantic-scholar -- uvx s2-mcp-server

Option 3: Claude Desktop (Windows)

Add to %APPDATA%\Claude\claude_desktop_config.json:

{
  "mcpServers": {
    "semantic-scholar": {
      "command": "uvx",
      "args": ["s2-mcp-server"],
      "env": {
        "SEMANTIC_SCHOLAR_API_KEY": "your-key-here"
      }
    }
  }
}

Option 4: Claude Desktop (macOS)

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "semantic-scholar": {
      "command": "uvx",
      "args": ["s2-mcp-server"],
      "env": {
        "SEMANTIC_SCHOLAR_API_KEY": "your-key-here"
      }
    }
  }
}

Option 5: pip / From Source

pip install s2-mcp-server
# or
git clone https://github.com/smaniches/semantic-scholar-mcp.git
cd semantic-scholar-mcp && pip install -e .

Option 6: Docker

docker pull ghcr.io/smaniches/semantic-scholar-mcp:latest
docker run -e SEMANTIC_SCHOLAR_API_KEY=your-key ghcr.io/smaniches/semantic-scholar-mcp

Option 7: Remote server (Streamable HTTP) — requires ≥ 1.5.0

# Serve MCP over HTTP at http://127.0.0.1:8000/mcp instead of stdio
# (--from pins the floor: uvx may otherwise reuse a cached older version)
uvx --from "s2-mcp-server>=1.5.0" s2-mcp-server --transport http

See Remote access (Streamable HTTP) for client configuration, per-request API keys, and deployment guidance.

Note: Get a free API key at semanticscholar.org/product/api. Without a key, you get rate-limited public access (1 req/sec).

Architecture

flowchart LR
  Client["MCP client<br/>(Claude Desktop, Claude Code,<br/>Cursor, Cline, Continue, …)"]
  subgraph Server ["s2-mcp-server (this package)"]
    direction TB
    FastMCP["FastMCP runtime<br/>(stdio / Streamable HTTP, lifespan)"]
    Tools["14 @mcp.tool functions<br/>(server.py)"]
    Models["Pydantic input models<br/>+ field sets (models.py)"]
    Validators["Paper-ID validator<br/>(validators.py)"]
    Cache["TTL cache<br/>(cache.py)"]
    Fmt["Markdown formatters<br/>(formatters.py)"]
    HTTP["httpx client<br/>+ rate limit + retry/backoff<br/>(client.py)"]
    Errors["Typed exceptions<br/>(errors.py)"]
    Log["Structured JSON logger<br/>(logging_config.py)"]
  end
  S2Graph["Semantic Scholar<br/>Graph API"]
  S2Recs["Semantic Scholar<br/>Recommendations API"]

  Client <-- "stdio or Streamable HTTP<br/>(JSON-RPC)" --> FastMCP
  FastMCP --> Tools
  Tools --> Models
  Tools --> Validators
  Tools --> Cache
  Tools --> HTTP
  Tools --> Fmt
  HTTP --> Errors
  HTTP --> Log
  HTTP -- "GET / POST<br/>x-api-key" --> S2Graph
  HTTP -- "GET / POST<br/>x-api-key" --> S2Recs

Module responsibilities (src/semantic_scholar_mcp/):

Module	Responsibility
`server.py`	FastMCP instance, 14 `@mcp.tool` registrations, lifespan, `main()` entry. Re-exports the helper surface for back-compat.
`transport.py`	Streamable HTTP transport: CLI/env parsing (`--transport http`), uvicorn wiring, and per-request API-key extraction (header / query param / Smithery config) into a request-scoped contextvar.
`client.py`	Shared `httpx.AsyncClient` singleton, per-tier rate limiter (1 req/s public, 10 req/s keyed), retry loop with exponential backoff + jitter on 429/503/timeout, HTTP→typed-exception mapping.
`models.py`	Pydantic input models per tool, `ResponseFormat` enum, the four tiered field-set constants (`PAPER_SEARCH_FIELDS`, `…_LITE`, `PAPER_BULK_SEARCH_FIELDS`, `PAPER_DETAIL_FIELDS`, `AUTHOR_FIELDS`).
`validators.py`	Pre-flight paper-ID validation. Rejects NUL bytes, `?`, `#`, path traversal; accepts the seven canonical ID formats.
`cache.py`	In-memory TTL cache (5 min, 200 entries, oldest-first eviction) for paper/author lookups within a session.
`formatters.py`	Markdown renderers for paper and author dicts, tuned for chat-surface readability.
`errors.py`	`SemanticScholarError` hierarchy: `AuthenticationError`, `RateLimitError`, `NotFoundError`, `ValidationError`, `ServerError`.
`logging_config.py`	One-JSON-per-line `StructuredFormatter` on stderr; safe to ship through any log aggregator.

Design choices worth knowing

Single httpx.AsyncClient per process. Created lazily, closed in the FastMCP lifespan teardown. Amortizes connection setup; respects keep-alive limits. The lifespan is reference-counted: under the Streamable HTTP transport the SDK enters it per request, so teardown only runs when the last holder exits.
Rate limit is enforced at the client, not the API. A semaphore + last-request timestamp ensures we never exceed the per-tier interval even when the MCP host issues tool calls in parallel.
Retry is bounded and jittered. Up to MAX_RETRIES = 3, base 1 s, capped at 30 s. Honors Retry-After when present.
Errors are typed. Status codes map onto a small exception hierarchy so callers can branch on AuthenticationError vs RateLimitError vs NotFoundError instead of parsing strings.
Input validation is pre-flight. Paper IDs are checked before any outbound request; bad IDs never hit the wire.
Version is single-source. __version__ is derived from importlib.metadata.version("s2-mcp-server"), so bumping pyproject.toml is sufficient; release-please bumps the manifest, server.json (×2 paths), CITATION.cff, and .zenodo.json in lockstep on every release.

Configuration

API Key Options

You can provide your API key in three ways:

Environment Variable (recommended for persistent use):
```
export SEMANTIC_SCHOLAR_API_KEY="your-api-key-here"
```
Per-request HTTP header (Streamable HTTP transport only): send x-api-key: your-key with each request — see Remote access (Streamable HTTP).
Per-Request Parameter (overrides env var):
```
{
  "api_key": "your-api-key-here"
}
```
Deprecated: per-request api_key is deprecated and will be removed in v2.0.0. Tool-call arguments may be visible in MCP transcripts, client logs, and the LLM's tool-call history. Use the SEMANTIC_SCHOLAR_API_KEY environment variable instead. See SECURITY.md for details.

Get a free API key at: https://www.semanticscholar.org/product/api

Claude Desktop Setup

Add to your Claude Desktop config file:

Windows: %APPDATA%\Claude\claude_desktop_config.json macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "semantic-scholar": {
      "command": "python",
      "args": ["-m", "semantic_scholar_mcp"],
      "env": {
        "SEMANTIC_SCHOLAR_API_KEY": "your-api-key-here"
      }
    }
  }
}

Then restart Claude Desktop.

Remote access (Streamable HTTP)

stdio remains the default transport. --transport http serves the same 14 tools over the MCP Streamable HTTP transport, which is what remote clients — claude.ai custom connectors, Smithery listings, mcp-remote bridges — connect to.

Requires s2-mcp-server ≥ 1.5.0. Earlier releases (≤ 1.4.0) do not parse CLI flags: they silently ignore --transport http and start a stdio server instead, never opening the port.

# Local HTTP endpoint at http://127.0.0.1:8000/mcp
# (--from pins the floor: uvx may otherwise reuse a cached older version)
uvx --from "s2-mcp-server>=1.5.0" s2-mcp-server --transport http

# Bind a public interface and custom port (only behind a TLS proxy — see Security)
uvx --from "s2-mcp-server>=1.5.0" s2-mcp-server --transport http --host 0.0.0.0 --port 8080

# Docker
docker run -p 8000:8000 ghcr.io/smaniches/semantic-scholar-mcp --transport http

Flags and environment variables

Flag	Env var	Default	Meaning
`--transport`	`MCP_TRANSPORT`	`stdio`	`stdio`, `http` (alias: `streamable-http`)
`--host`	`MCP_HOST`	`127.0.0.1`	Bind address (`0.0.0.0` in the Docker image)
`--port`	`MCP_PORT`, then `PORT`	`8000`	Bind port (`PORT` is honored for hosting platforms)
`--path`	`MCP_PATH`	`/mcp`	URL path of the MCP endpoint
—	`MCP_STATELESS_HTTP`	`true`	One independent server interaction per request (recommended)
—	`MCP_JSON_RESPONSE`	`true`	Plain JSON responses instead of SSE streams

CLI flags beat environment variables. The server is stateless and returns JSON by default — the configuration recommended for production Streamable HTTP deployments — and no tool relies on sessions, streaming, or server-initiated messages, so there is no functional trade-off.

Per-request API keys (bring your own key)

When served over HTTP, each request may carry its own Semantic Scholar API key; concurrent users never share or observe each other's keys. Sources, in precedence order:

x-api-key HTTP header (recommended)
SEMANTIC_SCHOLAR_API_KEY query parameter (Smithery session config)
api_key query parameter
Legacy base64 ?config= parameter (older Smithery deployments)

A request without a key falls back to the server's SEMANTIC_SCHOLAR_API_KEY environment variable, or to keyless public-tier access.

Client configuration

Claude Code

claude mcp add --transport http semantic-scholar http://127.0.0.1:8000/mcp \
  --header "x-api-key: your-key-here"

JSON config (clients that accept a url)

{
  "mcpServers": {
    "semantic-scholar": {
      "type": "http",
      "url": "http://127.0.0.1:8000/mcp",
      "headers": { "x-api-key": "your-key-here" }
    }
  }
}

claude.ai custom connectors require a public HTTPS URL and accept either authless servers or OAuth — API keys in the connector URL are not supported by claude.ai. Host the server with the key supplied server-side (SEMANTIC_SCHOLAR_API_KEY env var) and register the public /mcp URL as the connector.

Smithery lists remote servers by URL (smithery mcp publish <url>); the per-request key extraction above is compatible with Smithery session config out of the box.

Security notes

The HTTP transport performs no authentication of inbound callers. The default bind is loopback (127.0.0.1). Expose it publicly only behind a TLS-terminating reverse proxy, and prefer the x-api-key header over query parameters (URLs end up in access logs).
API keys are request-scoped, and the server itself never logs them. (A key placed in a URL query parameter can still appear in access logs, as noted above — prefer the x-api-key header.)
See SECURITY.md for the project's broader threat model.

Supported ID Formats

The server accepts the following paper identifier formats:

Format	Pattern	Example
Semantic Scholar ID	40-character hex	`649def34f8be52c8b66281af98ae884c09aef38b`
DOI	`DOI:xxx`	`DOI:10.1038/s41586-021-03819-2`
ArXiv	`ARXIV:xxx`	`ARXIV:2106.15928` or `ARXIV:2106.15928v2`
PubMed	`PMID:xxx`	`PMID:32908142`
Corpus ID	`CorpusId:xxx`	`CorpusId:215416146`
ACL	`ACL:xxx`	`ACL:P19-1285`
URL	`URL:xxx`	`URL:https://arxiv.org/abs/2106.15928`

Tools Reference

1. `semantic_scholar_search_papers`

Search for academic papers with advanced filters.

Parameters:

Parameter	Type	Required	Description
`query`	string	Yes	Search query (supports AND, OR, NOT operators and "phrase search")
`year`	string	No	Year filter: `"2024"`, `"2020-2024"`, or `"2020-"`
`fields_of_study`	string[]	No	Filter by fields: `["Computer Science", "Biology"]`
`publication_types`	string[]	No	Filter by type: `["Review", "JournalArticle"]`
`open_access_only`	boolean	No	Only return open access papers (default: false)
`min_citation_count`	integer	No	Minimum citation count
`limit`	integer	No	Max results 1-100 (default: 10)
`offset`	integer	No	Pagination offset (default: 0)
`response_format`	string	No	`"markdown"` or `"json"` (default: markdown)
`api_key`	string	No	Override environment API key

Example:

Search for "transformer attention mechanism" papers from 2023 with at least 100 citations

JSON Example:

{
  "query": "transformer attention mechanism",
  "year": "2023",
  "min_citation_count": 100,
  "fields_of_study": ["Computer Science"],
  "limit": 20
}

2. `semantic_scholar_get_paper`

Get detailed information about a specific paper.

Parameters:

Parameter	Type	Required	Description
`paper_id`	string	Yes	Paper ID in any supported format
`include_citations`	boolean	No	Include citing papers (default: false)
`include_references`	boolean	No	Include referenced papers (default: false)
`citations_limit`	integer	No	Max citations to return 1-100 (default: 10)
`references_limit`	integer	No	Max references to return 1-100 (default: 10)
`response_format`	string	No	`"markdown"` or `"json"` (default: markdown)
`api_key`	string	No	Override environment API key

Example:

Get details for DOI:10.1038/s41586-021-03819-2 including its top 20 citations

JSON Example:

{
  "paper_id": "DOI:10.1038/s41586-021-03819-2",
  "include_citations": true,
  "citations_limit": 20
}

3. `semantic_scholar_search_authors`

Search for academic authors by name.

Parameters:

Parameter	Type	Required	Description
`query`	string	Yes	Author name to search
`limit`	integer	No	Max results 1-100 (default: 10)
`offset`	integer	No	Pagination offset (default: 0)
`response_format`	string	No	`"markdown"` or `"json"` (default: markdown)
`api_key`	string	No	Override environment API key

Example:

Find author "Yoshua Bengio"

JSON Example:

{
  "query": "Yoshua Bengio",
  "limit": 5
}

4. `semantic_scholar_get_author`

Get author profile with publications.

Parameters:

Parameter	Type	Required	Description
`author_id`	string	Yes	Semantic Scholar author ID
`include_papers`	boolean	No	Include publications (default: true)
`papers_limit`	integer	No	Max papers to return 1-100 (default: 20)
`response_format`	string	No	`"markdown"` or `"json"` (default: markdown)
`api_key`	string	No	Override environment API key

Example:

Get author profile for author ID 1741101 with their top 50 publications

JSON Example:

{
  "author_id": "1741101",
  "include_papers": true,
  "papers_limit": 50
}

5. `semantic_scholar_recommendations`

Get AI-powered paper recommendations based on a seed paper.

Parameters:

Parameter	Type	Required	Description
`paper_id`	string	Yes	Seed paper ID in any supported format
`from_pool`	string	No	Recommendation pool: `"recent"` (default) or `"all-cs"`
`limit`	integer	No	Max recommendations 1-100 (default: 10)
`response_format`	string	No	`"markdown"` or `"json"` (default: markdown)
`api_key`	string	No	Override environment API key

Example:

Get recommendations based on paper 649def34f8be52c8b66281af98ae884c09aef38b

JSON Example:

{
  "paper_id": "ARXIV:1706.03762",
  "limit": 15
}

6. `semantic_scholar_bulk_papers`

Retrieve multiple papers in a single request (max 500).

Parameters:

Parameter	Type	Required	Description
`paper_ids`	string[]	Yes	List of paper IDs (max 500)
`response_format`	string	No	`"markdown"` or `"json"` (default: json)
`api_key`	string	No	Override environment API key

Example:

Retrieve these papers: DOI:10.1038/nature12373, ARXIV:2106.15928, PMID:32908142

JSON Example:

{
  "paper_ids": [
    "DOI:10.1038/nature12373",
    "ARXIV:2106.15928",
    "PMID:32908142"
  ]
}

7. `semantic_scholar_bulk_search`

Search papers with sorting and cursor-based pagination for large result sets. Unlike search_papers, supports a sort order and returns a token for paging through all results.

Parameters:

Parameter	Type	Required	Description
`query`	string	Yes	Search query
`sort`	string	No	Sort order, e.g. `"citationCount:desc"`, `"publicationDate:asc"`
`token`	string	No	Continuation token from a previous bulk_search response
`year`	string	No	Year filter: `"2024"`, `"2020-2024"`, `"2020-"`
`fields_of_study`	string[]	No	Filter by fields: `["Computer Science"]`
`publication_types`	string[]	No	Filter by type: `["Review", "JournalArticle"]`
`min_citation_count`	integer	No	Minimum citation count
`limit`	integer	No	Max results per page 1-1000 (default: 100)
`response_format`	string	No	`"markdown"` or `"json"` (default: markdown)
`api_key`	string	No	Override environment API key

JSON Example:

{
  "query": "graph neural networks",
  "sort": "citationCount:desc",
  "year": "2020-2024",
  "limit": 100
}

Returns: total result count, the page of papers, and a token for the next page (when more results exist).

8. `semantic_scholar_export_citation`

Export a citation for a paper in BibTeX format.

Parameters:

Parameter	Type	Required	Description
`paper_id`	string	Yes	Paper ID in any supported format
`format`	string	No	Citation format (currently only `"bibtex"`)
`api_key`	string	No	Override environment API key

JSON Example:

{
  "paper_id": "DOI:10.1038/s41586-021-03819-2",
  "format": "bibtex"
}

Returns: the BibTeX string for the requested paper.

9. `semantic_scholar_match_paper`

Find the single best paper matching a title string. Returns a numeric matchScore alongside the matched paper.

Parameters:

Parameter	Type	Required	Description
`query`	string	Yes	Paper title to match (1-500 chars)
`response_format`	string	No	`"markdown"` or `"json"` (default: markdown)
`api_key`	string	No	Override environment API key

JSON Example:

{
  "query": "Attention Is All You Need"
}

Returns: the best-matching paper plus its matchScore, or "No matching paper found." if no match.

10. `semantic_scholar_paper_authors`

Get full author profiles for a paper's authors (richer than the abbreviated author list returned by get_paper).

Parameters:

Parameter	Type	Required	Description
`paper_id`	string	Yes	Paper ID in any supported format
`limit`	integer	No	Max authors to return 1-1000 (default: 100)
`response_format`	string	No	`"markdown"` or `"json"` (default: markdown)
`api_key`	string	No	Override environment API key

JSON Example:

{
  "paper_id": "ARXIV:1706.03762",
  "limit": 25
}

Returns: the list of full author records for the paper.

11. `semantic_scholar_author_batch`

Retrieve multiple authors in a single request (max 1000).

Parameters:

Parameter	Type	Required	Description
`author_ids`	string[]	Yes	List of author IDs (1-1000)
`response_format`	string	No	`"markdown"` or `"json"` (default: json)
`api_key`	string	No	Override environment API key

JSON Example:

{
  "author_ids": ["1741101", "40348417", "144749327"]
}

Returns: counts of requested / retrieved, the retrieved author records, and a not_found list of IDs the API did not return.

12. `semantic_scholar_multi_recommend`

Get recommendations using multiple positive (and optional negative) example papers.

Parameters:

Parameter	Type	Required	Description
`positive_paper_ids`	string[]	Yes	Papers to find similar results for (1-100)
`negative_paper_ids`	string[]	No	Papers to dissimilate from (0-100)
`limit`	integer	No	Max recommendations 1-500 (default: 10)
`response_format`	string	No	`"markdown"` or `"json"` (default: markdown)
`api_key`	string	No	Override environment API key

JSON Example:

{
  "positive_paper_ids": ["ARXIV:1706.03762", "ARXIV:1810.04805"],
  "negative_paper_ids": ["DOI:10.1038/nature14539"],
  "limit": 20
}

Returns: the recommended papers plus an echo of the positive/negative seeds used.

13. `semantic_scholar_snippet_search`

Search within paper full text and return text snippets with surrounding context. Heavily rate-limited without an API key.

Parameters:

Parameter	Type	Required	Description
`query`	string	Yes	Search query for paper text (1-500 chars)
`paper_ids`	string[]	No	Limit search to specific papers (max 100)
`year`	string	No	Year filter: `"2024"`, `"2020-2024"`, `"2020-"`
`fields_of_study`	string[]	No	Filter by fields: `["Computer Science"]`
`min_citation_count`	integer	No	Minimum citation count
`limit`	integer	No	Max results 1-100 (default: 10)
`response_format`	string	No	`"markdown"` or `"json"` (default: markdown)
`api_key`	string	No	Override environment API key

JSON Example:

{
  "query": "scaling laws for language models",
  "year": "2022-2024",
  "limit": 20
}

Returns: matching snippets, each with the source paper title, section, and a short text excerpt.

14. `semantic_scholar_status`

Check server health and API connectivity status.

Parameters: None

Example:

Check Semantic Scholar API status

Response:

{
  "server": "semantic-scholar-mcp",
  "version": "<current package version>",
  "api_key_configured": true,
  "rate_tier": "authenticated (10 req/sec)",
  "timestamp": "2026-04-06T12:00:00.000000+00:00",
  "api_reachable": true,
  "rate_limited": false,
  "retry_after": null
}

Rate Limits

Tier	Requests/Second	How to Get
No API Key	1 req/sec	Default
API Key	10 req/sec	Sign up (free)
Academic Partner	10-100 req/sec	Apply via S2

Note: The client-side rate limiter enforces the intervals above. The upstream Semantic Scholar API may impose stricter limits during high-traffic periods.

The server automatically handles rate limiting with:

Request serialization to enforce minimum intervals
Exponential backoff retry for 429 (rate limit) and 503 (service unavailable) errors
Maximum 3 retries with jitter

Development

# Clone
git clone https://github.com/smaniches/semantic-scholar-mcp.git
cd semantic-scholar-mcp

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run tests with coverage
pytest --cov=src/semantic_scholar_mcp --cov-report=term-missing

# Type checking
mypy src/

Security

API keys are never persisted to disk by the server. When the server makes authenticated requests, the key is sent only to api.semanticscholar.org over HTTPS as the x-api-key header. No telemetry is sent to any third party. Under the default stdio transport the server runs locally on your machine; if you connect to a remotely hosted instance over Streamable HTTP, your per-request key also transits that endpoint's operator before being forwarded to Semantic Scholar — only send keys to remote endpoints you trust, and only over HTTPS.

Prefer the SEMANTIC_SCHOLAR_API_KEY environment variable over the per-request api_key tool parameter. The per-request parameter is deprecated (removal planned for v2.0.0) because tool-call arguments may be visible in MCP transcripts and client logs. See SECURITY.md for vulnerability reporting and the known-limitations list.

Related MCP servers by the same author

alphafold-sovereign-mcp — Model Context Protocol server for AlphaFold DB and 13 other biomedical data sources, with a local SQLite knowledge graph (pip install --pre alphafold-sovereign-mcp).
uniprot-mcp — Model Context Protocol server for UniProt Swiss-Prot and TrEMBL (pip install uniprot-mcp-server).

License

MIT License - see LICENSE file.

Author

Santiago Maniches

Founder & CEO, TOPOLOGICA LLC
ORCID: 0009-0005-6480-1987
LinkedIn: santiago-maniches
Website: topologica.ai

Contributing

Contributions welcome! Please read our Contributing Guidelines.

Support

Built by TOPOLOGICA LLC

Name		Name	Last commit message	Last commit date
Latest commit History 130 Commits
.github		.github
docs		docs
examples		examples
scripts		scripts
src/semantic_scholar_mcp		src/semantic_scholar_mcp
tests		tests
.dockerignore		.dockerignore
.editorconfig		.editorconfig
.gitattributes		.gitattributes
.gitignore		.gitignore
.mcp.json		.mcp.json
.pre-commit-config.yaml		.pre-commit-config.yaml
.release-please-manifest.json		.release-please-manifest.json
.zenodo.json		.zenodo.json
CHANGELOG.md		CHANGELOG.md
CITATION.cff		CITATION.cff
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
Dockerfile		Dockerfile
LICENSE		LICENSE
LIMITATIONS.md		LIMITATIONS.md
README.md		README.md
REVIEWER.md		REVIEWER.md
SECURITY.md		SECURITY.md
glama.json		glama.json
llms-install.md		llms-install.md
logo-white.png		logo-white.png
logo.png		logo.png
pyproject.toml		pyproject.toml
release-please-config.json		release-please-config.json
requirements-dev.lock		requirements-dev.lock
server.json		server.json
smithery.yaml		smithery.yaml

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Semantic Scholar MCP Server

Quick start

Provenance & supply chain

How it compares

Installation

Option 1: One-Line Install (Recommended)

Option 2: Claude Code

Option 3: Claude Desktop (Windows)

Option 4: Claude Desktop (macOS)

Option 5: pip / From Source

Option 6: Docker

Option 7: Remote server (Streamable HTTP) — requires ≥ 1.5.0

Architecture

Configuration

API Key Options

Claude Desktop Setup

Remote access (Streamable HTTP)

Flags and environment variables

Per-request API keys (bring your own key)

Client configuration

Security notes

Supported ID Formats

Tools Reference

1. semantic_scholar_search_papers

2. semantic_scholar_get_paper

3. semantic_scholar_search_authors

4. semantic_scholar_get_author

5. semantic_scholar_recommendations

6. semantic_scholar_bulk_papers

7. semantic_scholar_bulk_search

8. semantic_scholar_export_citation

9. semantic_scholar_match_paper

10. semantic_scholar_paper_authors

11. semantic_scholar_author_batch

12. semantic_scholar_multi_recommend

13. semantic_scholar_snippet_search

14. semantic_scholar_status

Rate Limits

Development

Security

Related MCP servers by the same author

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Languages

1. `semantic_scholar_search_papers`

2. `semantic_scholar_get_paper`

3. `semantic_scholar_search_authors`

4. `semantic_scholar_get_author`

5. `semantic_scholar_recommendations`

6. `semantic_scholar_bulk_papers`

7. `semantic_scholar_bulk_search`

8. `semantic_scholar_export_citation`

9. `semantic_scholar_match_paper`

10. `semantic_scholar_paper_authors`

11. `semantic_scholar_author_batch`

12. `semantic_scholar_multi_recommend`

13. `semantic_scholar_snippet_search`

14. `semantic_scholar_status`

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