Firecrawl MCP Server vs Pfc MCP
A side-by-side look at the Firecrawl MCP Server and Pfc MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Firecrawl MCP Server for search & data extraction work as a local process; choose Pfc MCP for research. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Firecrawl MCP Server when
- You need dedicated capabilities in the Search & Data Extraction domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
FIRECRAWL_API_KEY, HTTP_STREAMABLE_SERVER, FIRECRAWL_NO_SEARCH_FEEDBACK, FIRECRAWL_NO_ENDPOINT_FEEDBACK. - You want tools like
firecrawl_scrape, firecrawl_map, firecrawl_search.
Choose Pfc MCP when
- You need dedicated capabilities in the Research domain.
- Its auth model fits you: No auth required.
- You want tools like
itasca_browse_commands, itasca_browse_python_api, itasca_browse_reference.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Search & Data Extraction | Research |
| Quality signal | 90/100 · Excellent | 61/100 · Good |
| Install command | Confirmed | Not confirmed yet |
| Transport | Local subprocess (stdio) | — |
| Auth | API key required | No auth required |
| Pricing | Freemium | Free |
| Required env vars | FIRECRAWL_API_KEYHTTP_STREAMABLE_SERVERFIRECRAWL_NO_SEARCH_FEEDBACKFIRECRAWL_NO_ENDPOINT_FEEDBACK | None listed |
| Verified owner | Verified | Community listing |
| GitHub stars | 7,642 | 220 |
| Directory activity | 13 views 0 installs 0 upvotes | 3 views 0 installs 0 upvotes |
| Tools | 25 | 10 |
| Full listing | View Firecrawl MCP Server | View Pfc MCP |
Tools & capabilities
Firecrawl MCP Server tools 25
firecrawl_scrapeRetrieve and extract content from one supplied URL through Firecrawl. Use this when the request identifies a page and needs its content or defined fields. It can return markdown, HTML, links, screenshots, branding data, a targeted answer, or JSON matching a supplied schema; JSON is useful when the requested result has defined fields, while markdown preserves readable page content. This tool operates on a known page. For a set of pages use `firecrawl_crawl`, and to discover page URLs use `firecrawl_map` or `firecrawl_search`. Options include JavaScript render delay, cache age, main-content filtering, PII redaction, and lockdown cache-only retrieval. Browser actions may change the live page when interactive actions are enabled. Firecrawl may reuse recently indexed content instead of refetching the page, and the reuse window varies by domain. Set `maxAge: 0` to force a live fetch, or a smaller `maxAge` to bound how stale reused content may be. A successful response does not by itself confirm that the state it describes is still current. Returns the selected content formats and page metadata.firecrawl_mapEnumerate URLs indexed under one website through Firecrawl without fetching each page's content. Use this when the request asks for a site's URL inventory, when several relevant pages must be located, or when the desired page URL is unknown. An optional `search` term narrows the URL list, while sitemap, subdomain, query-parameter, and result-limit options control coverage. Returns matching URLs rather than page bodies. Retrieve one page with `firecrawl_scrape`; collect content across multiple pages with `firecrawl_crawl`.firecrawl_searchSearch web, news, or image sources and return ranked results. Operators include quoted phrases, `-term`, `site:host`, `inurl:term`, `intitle:term`, and `related:host`; the set is non-exhaustive. `includeDomains` and `excludeDomains` are mutually exclusive hostname filters; categories limit results to GitHub, research, PDF, or developer sources. For a programming question, add `categories: ["developer"]`. It searches an index of GitHub issues, merged pull requests, repository READMEs, and curated documentation sites, and returns the hits in `data.developer` beside the web results. `categories: ["research"]` restricts these web results to research-affiliated websites and returns page snippets. The `firecrawl_research_*` tools are a separate surface that searches paper abstracts and full text across biomedical (PubMed, bioRxiv, medRxiv) and arXiv literature. `scrapeOptions` can attach extracted page content; pages fetched this way use a fixed reuse window and ignore `maxAge`, so use `firecrawl_scrape` when a live fetch is required. Returns source-type result groups and usage metadata. Authenticated responses can include an `id` for optional search feedback.firecrawl_crawlStart a multi-page crawl at a website URL, poll it to a terminal state, and return the final status and collected data. Scope can be bounded with include/exclude paths, depth, page limit, subdomain/external-link controls, sitemap handling, delay, and scrape options. Crawl results can be large; use conservative limits when full-site coverage is unnecessary. Webhooks and interactive scrape actions are unavailable in safe mode. Returns the crawl ID, status, and page data.firecrawl_check_crawl_statusRetrieve the current status, progress, and available results for an existing crawl ID. This only reads Firecrawl job state and does not start or modify the crawl.firecrawl_extractDeprecated compatibility entry point. Use firecrawl_scrape once per known URL with formats: ["json"] and jsonOptions containing the prompt and schema. Use firecrawl_search or firecrawl_agent before Scrape when URLs are not known.firecrawl_agentStart an asynchronous web research job from a prompt, optional seed URLs, and an optional JSON schema. Use this for a requested synthesis across multiple sources when the task can wait for asynchronous completion. The agent can search, navigate, read pages, and assemble a structured result. This call returns only a job ID, not the research result. Read the job with `firecrawl_agent_status` until it reaches `completed` or `failed`; research commonly takes several minutes. If the job cannot finish within the task's available time, `firecrawl_search` and `firecrawl_scrape` can gather evidence synchronously.firecrawl_agent_statusRetrieve progress or final results for a `firecrawl_agent` job ID. A `processing` response is non-terminal and does not contain the final research result. Check again after 15–30 seconds until the status is `completed` or `failed`; complex jobs can take several minutes. If the job cannot finish within the task's available time, use `firecrawl_search` and `firecrawl_scrape` to complete the requested output. Returns job status, progress information, and result data when completed.firecrawl_interactOpen or reuse a live browser session to navigate a page, click controls, fill fields, or run browser code. Provide either `url` or `scrapeId`, and either a natural-language `prompt` or executable `code`; code can run as Bash, Python, or Node with a bounded timeout. This acts on the live site, so actions such as form submission can create persistent external side effects. Returns execution output, stdout/stderr, exit status, and session viewing URLs.firecrawl_interact_stopStop the live interact session associated with a `scrapeId` and release its resources. Returns a success confirmation.firecrawl_parseParse one supported document into markdown, HTML, links, summary, targeted answers, or JSON matching a schema. Supported inputs include common HTML, PDF, Word, RTF, OpenDocument, and spreadsheet files; PDF parsing can be bounded with `pdfOptions.maxPages`. Local MCP reads `filePath` from the server filesystem. Hosted MCP uses two calls: first provide `filePath` to receive upload instructions, upload locally, then call again with the returned `uploadRef`; do not send both fields together. Remote web URLs belong in `firecrawl_scrape`. Set `redactPII` to request redaction of personally identifiable information in the returned content. `zeroDataRetention` requires an eligible authenticated account; omit it for anonymous keyless use. Returns upload instructions for hosted phase one or parsed document content for the final call.firecrawl_monitor_createCreate a recurring scrape, crawl, or search monitor that compares each check with its retained predecessor. The simple form accepts `page`/`pages` or `queries` plus a plain-language `goal`; the advanced `body` form controls targets, schedule, change-tracking formats, judging, retention, webhook, and notifications. In the simple form, a `goal` is required. If `queries` contains one or more non-empty values and is supplied with `page`/`pages`, `queries` create the search target and page targets are ignored. A monitor schedules future network checks and can send configured email or webhook notifications. Returns the created monitor.- +13 more on the listing page
Pfc MCP tools 10
itasca_browse_commandsBrowse Itasca command documentation by path (like glob + cat). Navigation levels: - No command: All command categories overview - Category only (e.g., "ball"): List commands in category - Full command (e.g., "ball create"): Full documentation When to use: - You know the command category or exact command - You want to explore available commands Related tools: - itasca_query_command: Search commands by keywords (when path unknown) - itasca_browse_reference: Browse reference docs (e.g., "contact-models linear")itasca_browse_python_apiBrowse Itasca Python SDK documentation by path (like glob + cat).itasca_browse_referenceBrowse ITASCA reference documentation (syntax elements, model properties). Works across engines via the required ``software`` selector (pfc/flac/3dec). References are language elements used within commands, not standalone commands. Navigation levels: - No topic: All reference categories for the engine - Category (e.g., "constitutive-models"): List items in category - Full path (e.g., "constitutive-models mohr-coulomb"): Full documentation - Sub-item path (e.g., "plot-items zone contour"): Sub-item details When to use: - Need material/contact/joint model property names (kn, ks, fric, cohesion, friction, ...) - Need range filtering syntax (position, cylinder, group, id) - Need plot item configuration (contour, label, color-by, cut, transparency, legend) - Setting up model-assignment commands (e.g. "... cmodel assign ... property ...") - Using range filters in any command - Configuring "plot item create" commands Related tools: - itasca_browse_commands: Command syntax (e.g., "zone create") - itasca_query_command: Search commands by keywordsitasca_query_commandSearch Itasca command documentation by keywords (like grep). Returns matching command paths. Use itasca_browse_commands for full documentation. When to use: - You have keywords but don't know exact command path - Example: "ball create", "contact property", "model solve" Related tools: - itasca_browse_commands: Get full documentation for a known command path - itasca_browse_reference: Browse reference docs (e.g., "contact-models linear") - itasca_query_python_api: Search Python SDK by keywordsitasca_query_python_apiSearch Itasca Python SDK documentation by keywords (like grep). Returns matching API paths with signatures. Use itasca_browse_python_api for full documentation. When to use: - You have keywords but don't know exact API path - Example: "ball velocity", "create", "contact force" Related tools: - itasca_browse_python_api: Get full documentation for a known API path - itasca_query_command: Search Itasca commands by keywordsitasca_execute_taskSubmit a Python script file for asynchronous execution in the Itasca engine. Returns a task_id immediately; the script runs in the background. Companion tools manage the lifecycle: - itasca_check_task_status: poll output, progress, and final status - itasca_interrupt_task: cancel a running task - itasca_list_tasks: browse task history For synchronous, inline execution, use itasca_execute_code instead. While the task is cycling, itasca_execute_code shares the same __main__ namespace in the engine's main thread, so you can inspect or modify simulation state live — probe progress, tune parameters mid-run, swap callbacks, or trigger early termination via a sentinel variable. Submit with reasonable starting values and refine as the task runs. Console output from itasca.command() inside the script (table dumps, list output, command summaries) is captured into the task log alongside Python prints, visible through itasca_check_task_status. Script-writing rules: - Multi-line itasca.command("""...""") batches are normalized to one engine call per command, keeping the task interruptible mid-batch. Normalization recognizes itasca.command through its import name; call it through that name directly — rebinding via intermediate variables (`_it = itasca`) bypasses it and logs a bridge warning. - Pass each FISH definition block (`fish define` / `fish operator` / legacy bare `define`, through its terminating standalone `end`) whole, in ONE itasca.command() string; feeding one line-by-line leaves the engine blocked in interactive FISH mode until completed manually in the GUI console. Per-line loops are fine for ordinary commands. - `program call '<file>'` (.p3dat / .p2dat / .dat / ...) is supported: the bridge runs the file inline, one command per engine call, so the bridge stays reachable, the task stays interruptible, and the file's output lands in the task log command by command.itasca_check_task_statusCheck status and paginated output for a submitted Itasca task. Output combines Python prints and Itasca console output from itasca.command() calls (table dumps, list output, command summaries) interleaved in execution order. Use skip_newest / limit to paginate, or filter to keep only matching lines.itasca_list_tasksList tracked Itasca tasks with pagination.itasca_interrupt_taskRequest graceful interruption of a running Itasca task.itasca_execute_codeExecute Python code synchronously in the running Itasca engine process. Returns stdout and an optional result variable immediately. Code runs in the engine's main thread, sharing the same __main__ namespace as any running task — side effects persist and are immediately visible to the task on its next cycle. The tool stays responsive while a task submitted via itasca_execute_task is cycling (calls interleave at cycle gaps), so use it as a live REPL — nothing has to be pre-scripted into the task up front. Typical uses: - Query model state and read Itasca command output: itasca.command('ball list') etc. — table dumps, list output, and command summaries are captured and interleaved with Python prints in execution order - Live inspection and tuning during a running task: check forces or contact statistics, modify parameters, swap callbacks, set sentinel variables the task reads each cycle - Create and export plots: itasca.command('plot ...') Environment: the engine's embedded Python interpreter (Itasca 9+ → Python 3.10, pre-9 → Python 3.6 or older; the product+version is encoded in sys.executable, e.g. PFC900). When unsure, check sys.version_info before relying on newer syntax. Code-writing rules (shared with itasca_execute_task): - Multi-line itasca.command("""...""") batches are normalized to one engine call per command, keeping the bridge reachable mid-batch. Normalization recognizes itasca.command through its import name; call it through that name directly — rebinding via intermediate variables (`_it = itasca`) bypasses it and the output carries a bridge warning. - Pass each FISH definition block (`fish define` / `fish operator` / legacy bare `define`, through its terminating standalone `end`) whole, in ONE itasca.command() string; feeding one line-by-line leaves the engine blocked in interactive FISH mode until completed manually in the GUI console. Per-line loops are fine for ordinary commands. - `program call '<file>'` (.p3dat / .p2dat / .dat / ...) is supported: the bridge runs the file inline, one command per engine call, so the bridge stays reachable, the run stays interruptible, and the file's output arrives command by command. Synchronous semantics: the request blocks until the code finishes or hits the timeout (default 10s, max 600s), and output is returned in full. The call is not tracked by itasca_list_tasks and cannot be interrupted mid-execution. For cancellable, pollable, or background work, submit via itasca_execute_task instead.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Firecrawl MCP Server
{
"mcpServers": {
"firecrawl-firecrawl-mcp-server": {
"command": "npx",
"args": [
"-y",
"firecrawl-mcp"
],
"env": {
"FIRECRAWL_API_KEY": "YOUR_FIRECRAWL_API_KEY_HERE",
"HTTP_STREAMABLE_SERVER": "YOUR_HTTP_STREAMABLE_SERVER_HERE",
"FIRECRAWL_NO_SEARCH_FEEDBACK": "YOUR_FIRECRAWL_NO_SEARCH_FEEDBACK_HERE",
"FIRECRAWL_NO_ENDPOINT_FEEDBACK": "YOUR_FIRECRAWL_NO_ENDPOINT_FEEDBACK_HERE"
}
}
}
}
Pfc MCP
No confirmed install command for Pfc MCP yet — follow the setup steps linked from its listing page rather than a guessed package name.
Frequently asked questions
Firecrawl MCP Server is categorized under Search & Data Extraction and uses a local stdio subprocess. Pfc MCP belongs to Research and uses an install path we have not confirmed yet. Pick Firecrawl MCP Server for search & data extraction work and Pfc MCP for research.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client. Pfc MCP has no confirmed install command yet — follow its own setup instructions.
Firecrawl MCP Server is listed as freemium — a free tier with paid plans. Auth: api key required. Pfc MCP is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add firecrawl-firecrawl-mcp-server and yusong652-pfc-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Firecrawl MCP Server has a quality signal of 90/100 (Excellent) with 13 views, 0 installs and 7,642 GitHub stars. Pfc MCP has 61/100 (Good) with 3 views, 0 installs and 220 GitHub stars.