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Firecrawl MCP Server

Official Firecrawl MCP server — web search, scraping to clean data, and autonomous deep research.

@ai-supply
Installations49k
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Firecrawl MCP Server

The official Firecrawl MCP Server brings Firecrawl's web scraping and search capabilities to MCP-compatible AI agents and clients like Claude and Cursor.

It lets an agent search the web and get full page content, scrape any URL into clean structured data, interact with pages (click and navigate), and run autonomous deep-research tasks. It handles JavaScript-heavy sites and includes automatic retries and rate limiting for reliable extraction.

It is aimed at developers building agents that need clean, agent-ready context pulled from the live web.

Rating rank
#1
of 16 in Research
Install rank
#7
of 16 in Research
Security score
100/100 · A
safe
Security rank
#1
of 16 in Research
Installs
49k
cat avg 51k
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✓ Security: Safe · 100100/100 · grade Ascanned 34m ago
✓ no compromise signals11 risk-surface · 6/20 OWASP controls flagged

Only compromise signals — malicious or tampered code (leaked secrets, backdoors, a dropped executable) — reduce the score. Dangerous-by-capability traits are risk surface, expected for some capabilities. Every finding is mapped to the OWASP control it belongs to below.

What this capability can do · high confidence (static)
Tools (1)
firecrawl_check_crawl_status
⚑ filesystem⚑ network⚑ secrets
egress → smithery.ai., smithery.ai, www.knacklabs.ai, mcp.so, www.klavis.ai, mcp.firecrawl.dev, docs.firecrawl.dev, www.firecrawl.dev +15

Findings mapped to the OWASP Top 10 for LLM Applications (2025) and the OWASP Machine Learning Security Top 10. Expand any flagged control for the exact findings — compromise reduces the score; expected/risk-surface do not.

OWASP Top 10 for LLM Applications
⚠LLM03Supply Chainhigh
Vulnerable/compromised dependencies, models or archives in the artifact.
•Dependency manifest — 19 npm dependencies declared · firecrawl-firecrawl-mcp-server-2bab1cc/package.jsonrisk surface
•Vulnerable dependencies — 23 known vulnerabilities in: @modelcontextprotocol/sdk@1.18.0, ajv@6.12.6, axios@1.15.2, body-parser@2.2.0, esbuild@0.27.7, file-type@21.0.0, follow-redirects@1.15.11, form-data@4.0.5 (CWE-1395)risk surface
⚠LLM05Improper Output Handlinghigh
Code that pipes model/user output into shell, eval, SQL or paths unsafely.
•Suspicious code patterns — environment/secret exfiltration · firecrawl-firecrawl-mcp-server-2bab1cc/src/index.ts (CWE-200)risk surface
•Path traversal sequences — '../' present in content or name · firecrawl-firecrawl-mcp-server-2bab1cc/src/index.ts (CWE-22)risk surface
⚠LLM06Excessive Agencymedium
Over-broad tool/permission surface or unrestricted egress.
•External endpoints declared — 1 distinct host(s) · firecrawl-firecrawl-mcp-server-2bab1cc/.github/workflows/publish.ymlrisk surface
•External endpoints declared — 2 distinct host(s) · firecrawl-firecrawl-mcp-server-2bab1cc/Dockerfilerisk surface
•Broad capability surface — 3 high-impact capability categories referenced — verify least-privilege · firecrawl-firecrawl-mcp-server-2bab1cc/README.md (CWE-272)risk surface
•External endpoints declared — 17 distinct host(s) · firecrawl-firecrawl-mcp-server-2bab1cc/README.mdrisk surface
•External endpoints declared — 3 distinct host(s) · firecrawl-firecrawl-mcp-server-2bab1cc/docker/nginx.confrisk surface
•External endpoints declared — 5 distinct host(s) · firecrawl-firecrawl-mcp-server-2bab1cc/src/fastmcp/FastMCP.tsrisk surface
•External endpoints declared — 7 distinct host(s) · firecrawl-firecrawl-mcp-server-2bab1cc/src/index.tsrisk surface
⚠LLM10Unbounded Consumptionmedium
Unbounded loops/recursion causing DoS or runaway cost.
Enforced at runtime by the gateway (rate limits + spend caps + size caps); static check flags unbounded loops.
•Potentially unbounded loop — an infinite loop (while True / while(1) / for(;;)) may cause runaway consumption · firecrawl-firecrawl-mcp-server-2bab1cc/src/index.ts (CWE-835)risk surface
§LLM09MisinformationGovernance
Artifacts designed to produce false/deceptive output.
Detectable only by runtime behavioral evaluation; addressed via responsible-use attestation.
✓LLM01Prompt InjectionPassed
✓LLM02Sensitive Information DisclosurePassed
✓LLM04Data and Model PoisoningPassed
Backdoors/poisoning in training data or serialized models.
Behavioral poisoning needs model execution; static check covers unsafe serialization + dataset skew only.
✓LLM07System Prompt LeakagePassed
✓LLM08Vector and Embedding WeaknessesPassed
PII or plaintext source leakage in embedding/vector exports.
Embedding inversion/poisoning is largely runtime; static check covers PII in vector exports.
OWASP Machine Learning Security Top 10
⚠ML06AI Supply Chainhigh
Compromised PyPI/npm packages, typosquats, unsafe serialized models.
•Dependency manifest — 19 npm dependencies declared · firecrawl-firecrawl-mcp-server-2bab1cc/package.jsonrisk surface
•Vulnerable dependencies — 23 known vulnerabilities in: @modelcontextprotocol/sdk@1.18.0, ajv@6.12.6, axios@1.15.2, body-parser@2.2.0, esbuild@0.27.7, file-type@21.0.0, follow-redirects@1.15.11, form-data@4.0.5 (CWE-1395)risk surface
⚠ML09Output Integrityhigh
Middleware tampering with model outputs in transit.
Gateway enforces TLS + response integrity; static check flags output-rewriting code.
•Suspicious code patterns — environment/secret exfiltration · firecrawl-firecrawl-mcp-server-2bab1cc/src/index.ts (CWE-200)risk surface
•Path traversal sequences — '../' present in content or name · firecrawl-firecrawl-mcp-server-2bab1cc/src/index.ts (CWE-22)risk surface
§ML01Input Manipulation (Adversarial)Governance
Models vulnerable to adversarial perturbations.
Requires runtime robustness evaluation; addressed via publisher robustness attestation.
§ML03Model InversionGovernance
Training data reconstructable from a model's outputs.
Runtime/evaluation property; addressed via model-card data-provenance + DP attestation.
§ML04Membership InferenceGovernance
Determining whether a record was in the training set.
Runtime/evaluation property; addressed via overfitting disclosure + DP attestation.
§ML08Model SkewingGovernance
Models trained on skewed data producing biased output.
Requires fairness evaluation; addressed via model-card bias/limitations disclosure.
✓ML02Data PoisoningPassed
Poisoned training datasets with triggers or anomalous distributions.
Static check covers trigger phrasing, PII and label skew; full poisoning detection is runtime.
✓ML05Model TheftPassed
Unlicensed re-distribution / license-incompatible derivatives.
Static check verifies license declaration; extraction throttling is runtime.
✓ML07Transfer Learning AttackPassed
Backdoored base models / LoRA adapters propagating to derivatives.
Backdoor detection needs behavioral probing; static check covers unsafe serialization + provenance.
✓ML10Model Poisoning (Weights)Passed
Tampered model weight files; integrity must be verifiable.
Static check enforces safe formats + records a content hash for downstream verification.
Other findings (5) · hygiene / uncategorized
•Unrecognized file type — '.gitignore' is not on the allowlist · firecrawl-firecrawl-mcp-server-2bab1cc/.gitignorerisk surface
•Unrecognized file type — '.prettierrc' is not on the allowlist · firecrawl-firecrawl-mcp-server-2bab1cc/.prettierrcrisk surface
•Unrecognized file type — '.?' is not on the allowlist · firecrawl-firecrawl-mcp-server-2bab1cc/Dockerfilerisk surface
•Unrecognized file type — '.service' is not on the allowlist · firecrawl-firecrawl-mcp-server-2bab1cc/Dockerfile.servicerisk surface
•Unrecognized file type — '.conf' is not on the allowlist · firecrawl-firecrawl-mcp-server-2bab1cc/docker/nginx.confrisk surface
✔ verified source · pinned firecrawl-firecrawl-mcp-server-2bab1cc · changed since last scan · +egress smithery.ai., smithery.ai, www.knacklabs.ai, mcp.so, www.klavis.ai, docs.cursor.com, img.shields.io, insiders.vscode.dev, firecrawl.your-domain.com, caw.tech, glama.ai, static.modelcontextprotocol.io, example.com.
Check against a policy

The same gate an agent runs before installing (POST /api/v1/trust/firecrawl-mcp-server/check). Click a policy:

Consume Firecrawl MCP Server programmatically. Authenticate with an API key or session — see Authorize an agent.

# Agents: CHECK BEFORE YOU INSTALL (no auth) — score, grade, level, capability manifest
curl https://ai-supply.store/api/v1/trust/firecrawl-mcp-server

# Gate against your org policy (returns { pass, violations })
curl -X POST https://ai-supply.store/api/v1/trust/firecrawl-mcp-server/check \
  -H "Content-Type: application/json" \
  -d '{"minGrade":"B","denyPermissions":["shell"],"denyUnknownEgress":true}'

# CLI
npx ai-supply add firecrawl-mcp-server

# REST (install → download)
curl -X POST https://ai-supply.store/api/v1/listings/firecrawl-mcp-server/install \
  -H "Authorization: Bearer $AIM_KEY"

# MCP tool
install_listing({ "slug": "firecrawl-mcp-server" })
OpenAPI spec →
vlatest
✓ Security: Safe · 1005h ago

Curated mirror — latest upstream source. See the repository for tagged releases.

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