What kind of provenance or supply chain guarantees does this server provide?

Every release includes verifiable supply-chain provenance such as Sigstore-signed SLSA build provenance attestations, PEP 740 attestations on PyPI uploads, and a CycloneDX SBOM to prove the artifact was built from the source repository.

How does this server compare to calling the Semantic Scholar REST API directly?

This server provides typed MCP tools that handle batching, pagination, bidirectional citation graph traversal, and snippet search with context, which would otherwise require manual implementation when calling the REST API directly.

Which MCP clients are compatible with this server?

It is compatible with MCP clients such as Claude Desktop, Claude Code, Cursor, Cline, and Continue.

How can I verify the authenticity of the distributed packages or container images?

You can verify the wheel, source distributions, and container images using GitHub CLI attestation verification commands provided in the documentation.

Semantic Scholar MCP

researchsemantic-scholaracademic-paperscitation-graphrecommendations

MCP server providing 14 typed tools for Semantic Scholar data access including search, retrieval, citation graph, and recommendations.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "smaniches-semantic-scholar-mcp": {
      "command": "uvx",
      "args": [
        "s2-mcp-server"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Overview

This MCP server offers direct access to over 200 million academic papers from Semantic Scholar via 14 typed tools. It supports paper and author retrieval, citation graph traversal in both directions, snippet search with context, and personalized recommendations. Use this server to integrate comprehensive academic research capabilities into any MCP-compatible client without handling raw API requests or pagination manually.

Use cases

Search academic papers with full-text snippet context

Retrieve detailed paper and author profiles

Traverse citation and reference graphs bidirectionally

Obtain paper and author recommendations

Perform bulk queries on papers and authors

Key features

14 typed MCP tools for research workflows

Access to 200M+ Semantic Scholar papers

Citation graph traversal (citations and references)

Bulk paper and author retrieval

Snippet search with surrounding context

No API key required for limited rate; optional key for higher rate

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Semantic Scholar MCP.

Extracted Tool Capabilities

14 typed MCP tools for research workflows

Access to 200M+ Semantic Scholar papers

Citation graph traversal (citations and references)

Bulk paper and author retrieval

Snippet search with surrounding context

No API key required for limited rate; optional key for higher rate

Documentation Overview

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

bash

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` (`build` job)
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 141–147)
PEP 740 attestations	the PyPI upload itself carries Sigstore-backed attestations under Trusted Publishing	`publish.yml` — `attestations: true` (`publish-pypi` job)
CycloneDX SBOM	a machine-readable bill of materials, generated in an unprivileged job from the exact wheel's statically resolved dependency metadata (wheels only, none of it executed), SHA-256-bound to that wheel, then attested against the wheel alone	`publish.yml` — `cyclonedx-py` + `scripts/release_sbom.py` (`sbom` job) + `actions/attest-sbom` (`attest-sbom` job)
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:

bash

# 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 429/502/503/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)

bash

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

Option 2: Claude Code

Terminal

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

Option 3: Claude Desktop (Windows)

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

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:

config.json

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

Option 5: pip / From Source

Terminal

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

Terminal

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

bash

# 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

mermaid

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"]

Read the full README →View source on GitHub →

Related MCP Servers

View all in Research View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

Last commit

18d ago

Most recent push to the default branch.

Directory activity

2 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Semantic Scholar MCP

No API key is required for public access with a rate limit of 1 request per second. Setting SEMANTIC_SCHOLAR_API_KEY increases the rate limit to 10 requests per second.

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Technical Specs & Signals

CategoryResearch

PricingFree

52Quality signal: Good · 52/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools23/30

Adoption & activity6/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 22d ago via OSV.dev · s2-mcp-server (PyPI)

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More in 🔬 Research →Best MCP servers for Research →Alternatives to Semantic Scholar MCP →Install in Claude Desktop Install in Cursor Install in VS Code

Semantic Scholar MCP

researchsemantic-scholaracademic-paperscitation-graphrecommendations

MCP server providing 14 typed tools for Semantic Scholar data access including search, retrieval, citation graph, and recommendations.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "smaniches-semantic-scholar-mcp": {
      "command": "uvx",
      "args": [
        "s2-mcp-server"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Overview

Use cases

Search academic papers with full-text snippet context

Retrieve detailed paper and author profiles

Traverse citation and reference graphs bidirectionally

Obtain paper and author recommendations

Perform bulk queries on papers and authors

Key features

14 typed MCP tools for research workflows

Access to 200M+ Semantic Scholar papers

Citation graph traversal (citations and references)

Bulk paper and author retrieval

Snippet search with surrounding context

No API key required for limited rate; optional key for higher rate

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Semantic Scholar MCP.

Extracted Tool Capabilities

14 typed MCP tools for research workflows

Access to 200M+ Semantic Scholar papers

Citation graph traversal (citations and references)

Bulk paper and author retrieval

Snippet search with surrounding context

No API key required for limited rate; optional key for higher rate

Documentation Overview

Semantic Scholar MCP Server

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

Quick start

bash

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

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` (`build` job)
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 141–147)
PEP 740 attestations	the PyPI upload itself carries Sigstore-backed attestations under Trusted Publishing	`publish.yml` — `attestations: true` (`publish-pypi` job)
CycloneDX SBOM	a machine-readable bill of materials, generated in an unprivileged job from the exact wheel's statically resolved dependency metadata (wheels only, none of it executed), SHA-256-bound to that wheel, then attested against the wheel alone	`publish.yml` — `cyclonedx-py` + `scripts/release_sbom.py` (`sbom` job) + `actions/attest-sbom` (`attest-sbom` job)
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:

bash

# 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

How it compares

	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 429/502/503/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)

bash

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

Option 2: Claude Code

Terminal

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

Option 3: Claude Desktop (Windows)

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

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:

config.json

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

Option 5: pip / From Source

Terminal

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

Terminal

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

bash

# 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

mermaid

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"]

Read the full README →View source on GitHub →

Related MCP Servers

View all in Research View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

Last commit

18d ago

Most recent push to the default branch.

Directory activity

2 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Semantic Scholar MCP

No API key is required for public access with a rate limit of 1 request per second. Setting SEMANTIC_SCHOLAR_API_KEY increases the rate limit to 10 requests per second.

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

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Markdown (GitHub README)

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Technical Specs & Signals

CategoryResearch

PricingFree

52Quality signal: Good · 52/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools23/30

Adoption & activity6/15

Community engagement0/10

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 22d ago via OSV.dev · s2-mcp-server (PyPI)

★ Featured

Moxie Docs MCP

MCP & Agent Skills for Automated Documentation, and codebase conventions + context

Explore Server →

Own this project?

Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

Claim & get free dofollow

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Add our SVG badge (dark/light directory styles) or embeddable widget to your site.

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More in 🔬 Research →Best MCP servers for Research →Alternatives to Semantic Scholar MCP →Install in Claude Desktop Install in Cursor Install in VS Code