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Side-by-side MCP evidence comparison
Evidence fieldFirecrawl MCPMCP100 SelectedHugging Face MCPMCP100 Selected
Task fit
Best for
  • Scraping and extracting public web pages
  • Search, crawl, map, batch, and research workflows
  • Teams already using Firecrawl API limits and governance
  • Searching models, datasets, Spaces, papers, and Hugging Face documentation
  • Exploring Hub metadata from an MCP-compatible assistant
  • Running explicitly selected Hugging Face tools in controlled research workflows
Not ideal for
  • Simple known-page fetches that do not justify a paid API
  • Sites whose terms or access controls prohibit automated collection
  • Workflows requiring guaranteed freshness or extraction accuracy
  • Highly regulated data or confidential prompts sent to unreviewed community Spaces
  • Unattended Jobs, sandbox execution, or repository writes
Avoid when
  • You cannot govern which URLs the agent may access
  • The workflow may collect personal, confidential, copyrighted, or access-controlled content without review
  • Unexpected API-credit consumption is unacceptable
  • Dynamic community Space discovery is enabled without tool-by-tool review
  • The Hugging Face token grants more repository or compute access than needed
  • Model, dataset, or Space content can directly trigger privileged tools
Provenance
Provenance details

First-party MCP

Firecrawl · Publisher source ↗

First-party MCP

Hugging Face · Publisher source ↗

Maintenance
Maintenance details

Repo: Aug 12, 2026

Package: Aug 12, 2026

Repo: Aug 14, 2026

Package: Not documented

Popularity evidence
GitHub stars

7,234

GitHub stars · checked 2026-08-14T18:46:26.000Z

273

GitHub stars · checked 2026-08-14T18:46:26.000Z

30-day package downloads

412,488

30-day package downloads · checked 2026-08-14T18:46:26.000Z

No reliable download data
External adoption evidence
  • github: repository stars: 7,234Exact attributable signal.github: repository stars · Admission snapshot · checked 2026-08-14T18:46:26.000ZEvidence source ↗
  • github: repository stars: 273Exact attributable signal.github: repository stars · Admission snapshot · checked 2026-08-14T18:46:26.000ZEvidence source ↗
Client coverage
Client coverage details
Claude Code✓ Local stdio
Claude Desktop✓ Local stdio
Codex✓ Local stdio
VS Code✓ Local stdio
Cursor✓ Local stdio
OpenCode✓ Local stdio
Claude Code✓ Streamable HTTP
Claude Desktop✓ Streamable HTTP
Codex✓ Streamable HTTP
VS Code✓ Streamable HTTP
Cursor✓ Streamable HTTP
OpenCode✓ Streamable HTTP
Client coverage noteLocal stdio runs on your computer. Streamable HTTP connects to a remotely hosted MCP server.
Access and data
AuthenticationCloud and local-package configurations use FIRECRAWL_API_KEY. Official docs also show hosted MCP URLs containing the key; environment-variable or protected input handling is safer than embedding the key in a URL.The hosted server supports browser login through `https://huggingface.co/mcp?login` or a Hugging Face bearer token. Use a fine-grained or read token unless writes or compute are explicitly required.
CostMCP calls consume the account's standard Firecrawl API credits and rate limits. Search, crawl, batch, and agent operations can consume more resources than single-page scraping; current plan pricing applies.Hub search and the open-source server have no separately documented MCP fee. Hugging Face Jobs, sandboxes, inference, storage, hardware-backed Spaces, and the AI client can incur normal account charges.
PermissionsThe MCP can initiate outbound requests to user- or model-selected URLs and invoke Firecrawl scrape, search, crawl, map, extraction, batch, and research capabilities according to enabled tools and account limits.Base tools search and navigate Hugging Face Hub resources and documentation. Optional tools can create and write repositories, manage sandbox files, run or schedule Jobs, and invoke selected or dynamically discovered community Spaces, bounded by the authenticated Hugging Face token and configured tool set.
Data handlingURLs, queries, extraction schemas, and retrieved page content are processed by the configured Firecrawl service. Cloud mode sends them to Firecrawl; self-hosted mode follows the operator's deployment and any configured model/provider dependencies.Queries and results pass through Hugging Face's hosted MCP service. Community Space calls send their arguments to the selected Space and return its outputs to the client. Jobs and sandboxes can process files and compute inputs on Hugging Face infrastructure.
Limitations
Tradeoffs
  • Broad scrape, crawl, search, and autonomous-agent tools are powerful but enlarge prompt-injection, compliance, and cost exposure.
  • Cloud mode is easy to configure; self-hosting adds operational burden.
  • Remote URL forms that embed an API key are convenient but can leak through configuration, logs, screenshots, or history.
  • The hosted endpoint makes Hub discovery easy, while optional community Gradio tools have independent publishers, behavior, and data handling.
  • Built-in Jobs, sandboxes, and repository contribution tools add useful compute and write capabilities but materially increase cost and impact.
  • Tool selection is configurable in Hugging Face MCP settings and should remain minimal.
Risk contextMain risks are prompt injection from untrusted pages, collection-policy violations, sensitive URL/query disclosure, API-key leakage, and agent-driven credit spend. Use URL allow-lists, low limits, human approval, and a dedicated low-budget key.Begin with search-only tools and a least-privilege token. Disable dynamic Spaces, repository writes, Jobs, and sandboxes unless separately approved; review every community Space as third-party code and never send secrets or regulated data. This documentary review does not claim MCP100 execution testing.
Evidence date
Editorial review2026-07-242026-07-24
Candidate evidence2026-08-14T18:46:26.000Z2026-08-14T18:46:26.000Z

Popularity, maintenance, fit, permissions, and client support are independent evidence fields.

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