| FMRS | 44 / 100 · D | 75 / 100 · B |
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| Reliability | 3 / 20 | 13 / 20 |
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| Security and permissions | 10 / 20 | 12 / 20 |
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| Maintenance | 10 / 20 | 16 / 20 |
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| Documentation | 13 / 20 | 17 / 20 |
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| Setup experience | 8 / 20 | 17 / 20 |
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| Best for | - Users who want the control loop and state kept on their device
- Users with llama.cpp, Ollama, LM Studio, or another OpenAI-compatible model backend
- Developers needing browser, filesystem, document, and task automation
- Technical users willing to review approvals, traces, and network egress
| - Scenarios needing clean, structured web context fed to an AI assistant
- Users already on the Firecrawl platform who want to call its scraping capability directly via MCP
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| Not for | - Users looking for a standalone MCP server that can be installed directly into an MCP client
- Production integrations requiring stable APIs, because the project is still a developer preview
- Environments that cannot allow agent access to browsers, files, shells, or networks
- Systems without Node.js, Chromium, git, or an accessible model backend
| - Simple static-page scraping where you don't want to depend on a third-party API and incur call costs
- Sites that explicitly disallow automated access (robots.txt)
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| Required permissions | - Read and write access to the local state directory and SQLite databases
- Permission to run approved shell commands and perform some process operations
- Access to the configured Chromium browser, browser profile, and websites
- Network access to configured llama-server, cloud models, search providers, or HTTP endpoints
- Permissions required by external MCP servers whose tools are invoked
- Optional macOS Accessibility, Screen Recording, Automation, or Reminders permissions
| - Requires a Firecrawl API key to call; cost and quota are governed by the Firecrawl account
- firecrawl_agent/firecrawl_interact perform automated browser interaction, which may trigger login or form-submission flows on the target site
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| Risks and side effects | - Browser navigation, HTTP tools, cloud models, search providers, MCP, Telegram, update checks, and analytics can create network egress
- Shell commands and skills inherit the agent process environment and may access `.env` secrets
- Traces and `.env` under the state directory should be treated as sensitive; the project says redaction and environment filtering are not complete isolation
- Filesystem writes, patches, archive extraction, process termination, HTTP requests, and untrusted MCP tools are policy-gated, but approval errors can still cause harm
- The project is a developer preview, so commands, configuration, and behavior may change
| - Bulk crawl/map tools can generate significant request volume against a target site — respect the site's rate limits and terms of service
- firecrawl_agent's interactive action chain is longer — define task boundaries clearly before running it to avoid accidentally triggering actions on a sensitive site
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| Supported clients | | Claude Desktop, VS Code, Cursor, Windsurf, Zed, Amp |
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| Tools | 0 | 11 |
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