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sposer

mcp-fetch

by sposer
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Offline Deployment

If you need to run this server in an offline environment (where playwright install cannot access the internet), follow these steps:

  1. On an online machine: Run the provided helper script to download the necessary browser binaries (Chromium) to a local directory (libs/browsers).

    This script automatically detects the required Playwright revision and downloads binaries for both Windows (win64) and Linux.

    uv run scripts/download_browsers.py

    This will create a libs/browsers directory containing the browser binaries (e.g., chromium-<revision>).

  2. Transfer files: Copy the entire project (or the installed package) AND the libs/browsers directory to your offline machine.

  3. Configure environment: On the offline machine, set the PLAYWRIGHT_BROWSERS_PATH environment variable to point to the libs/browsers directory before running the server.

    Windows (PowerShell):

    $env:PLAYWRIGHT_BROWSERS_PATH = "C:\path\to\mcp-fetch\libs\browsers"
mcp-fetch

    Linux/macOS:

    export PLAYWRIGHT_BROWSERS_PATH=/path/to/mcp-fetch/libs/browsers
mcp-fetch

    MCP Client Config (e.g., Claude/Trae): Add the environment variable to your MCP settings.

    {
  "mcpServers": {
    "fetch": {
      "command": "mcp-fetch",
      "args": [],
      "env": {
        "PLAYWRIGHT_BROWSERS_PATH": "E:\\Private\\Mcp\\fetch\\libs\\browsers",
        "MCP_FETCH_AUTO_INSTALL_PLAYWRIGHT": "0"
      }
    }
  }
}

    Note: Setting MCP_FETCH_AUTO_INSTALL_PLAYWRIGHT=0 prevents the server from attempting to download browsers if they are missing, which fails immediately in offline mode.

Available Tools

2 tools
fetch_pageA

Fetch/Crawl a dynamic web page and convert to Markdown (supports JavaScript).

Use this tool to:

  1. Crawl/Scrape content from modern web pages (React, Vue, etc.)

  2. Get full page content after JavaScript rendering

  3. Download large page content via chunked streaming

Protocol:

  1. Start: Provide url (required) → returns transfer_id + first chunk

  2. Continue: Provide transfer_id + offset → returns next chunk

Args:

  • url: Target http(s) URL (required for phase 1)

  • to_markdown: Convert HTML to Markdown (default: True)

  • wait_selector: CSS selector to wait for before capturing content

  • Optional: headers, query, timeout_ms, max_scrolls, min/max_delay_ms, proxy/pool, user_agent, chunk_bytes

  • Cursor: transfer_id, offset (for phase 2)

Returns:

  • Chunk: chunk_text or chunk_base64, next_offset, done, truncated

  • Meta: transfer_id, status, headers, final_url, content_type, elapsed_ms

  • Size: available_bytes, total_bytes

ParametersJSON Schema
NameRequiredDescriptionDefault
urlNo
headersNo
queryNo
timeout_msNo
to_markdownNo
wait_selectorNo
max_scrollsNo
min_delay_msNo
max_delay_msNo
proxyNo
proxy_poolNo
user_agentNo
chunk_bytesNo
transfer_idNo
offsetNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the two-phase protocol (start/continue), chunked streaming behavior, and various operational parameters like timeout, delays, and proxy support. It doesn't mention rate limits or authentication requirements, but covers most key behavioral aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (use cases, protocol, args, returns) but could be more concise. Some information is repeated (e.g., chunked streaming mentioned in both use cases and protocol), and the parameter list includes some redundant formatting. Overall, it's efficiently organized but not maximally concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (15 parameters, 0% schema coverage, no annotations) and the presence of an output schema, the description provides comprehensive context. It explains the tool's purpose, usage scenarios, operational protocol, parameter semantics, and return structure, making it complete enough for effective use despite the lack of structured documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage and 15 parameters, the description provides excellent parameter context. It explains the purpose of key parameters (url, to_markdown, wait_selector), categorizes them as required/optional/cursor parameters, and gives semantic meaning to many parameters that would otherwise be undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool fetches/crawls dynamic web pages and converts them to Markdown, specifying support for JavaScript rendering. It distinguishes from the sibling 'http_request' tool by emphasizing dynamic content handling and chunked streaming for large pages.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly lists three use cases (crawling modern web pages, getting JavaScript-rendered content, downloading large content via streaming) and outlines a two-phase protocol. It provides clear guidance on when to use this tool versus alternatives by highlighting its unique capabilities.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

http_requestA

Perform a generic HTTP request (GET, POST, PUT, DELETE, etc) for APIs or raw data.

Use this tool when:

  1. You need to call a REST API (JSON/XML)

  2. You need to use HTTP methods other than GET (POST, PUT, DELETE)

  3. You want to download a raw file without rendering (PDF, Image, etc)

Note: For GET requests to renderable web pages, prefer fetch_page which handles dynamic content and JavaScript.

Protocol:

  1. Start: Provide url (required) → returns transfer_id + first chunk

  2. Continue: Provide transfer_id + offset → returns next chunk

ParametersJSON Schema
NameRequiredDescriptionDefault
urlNo
methodNoGET
headersNo
queryNo
bodyNo
json_bodyNo
timeout_msNo
to_markdownNo
chunk_bytesNo
transfer_idNo
offsetNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the two-phase protocol (start with URL, continue with transfer_id+offset) and chunked transfer behavior. It mentions timeout_ms and chunk_bytes parameters in the schema but doesn't fully explain their behavioral implications. The description doesn't cover authentication requirements, rate limits, or error handling, which would be helpful for a generic HTTP tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections: a purpose statement, numbered usage guidelines, a note about alternatives, and a protocol explanation. Every sentence serves a distinct purpose with zero waste. The information is front-loaded with the most important guidance appearing first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (11 parameters, no annotations, but with output schema), the description provides good contextual coverage. It explains the core purpose, when to use it, when to use alternatives, and the two-phase protocol. The existence of an output schema means the description doesn't need to explain return values. However, for a generic HTTP tool with many parameters, more guidance on parameter usage would be beneficial.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage for 11 parameters, the description provides minimal parameter semantics. It mentions 'url (required)' and the two-phase protocol involving 'transfer_id' and 'offset', but doesn't explain the purpose or usage of most other parameters like method, headers, query, body, json_body, timeout_ms, to_markdown, or chunk_bytes. The description adds some value but doesn't adequately compensate for the complete lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as performing generic HTTP requests for APIs or raw data, specifying multiple HTTP methods (GET, POST, PUT, DELETE, etc.). It explicitly distinguishes from its sibling tool 'fetch_page' by noting that tool is for renderable web pages with dynamic content and JavaScript, while this tool is for REST APIs and raw file downloads.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidelines with three numbered scenarios: calling REST APIs, using non-GET HTTP methods, and downloading raw files. It also includes a clear 'Note' section specifying when NOT to use this tool (for GET requests to renderable web pages) and explicitly names the alternative tool 'fetch_page'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.4/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: fetch_page is for scraping dynamic web pages with JavaScript rendering and converting to Markdown, while http_request is for generic HTTP requests to APIs or raw files. The descriptions explicitly note when to use each tool, eliminating any overlap or confusion.

Naming Consistency5/5

Both tools follow a consistent verb_noun pattern (fetch_page and http_request) with clear, descriptive names that match their functions. There are no deviations or mixed conventions in the naming style.

Tool Count3/5

With only 2 tools, the server feels thin for a general-purpose HTTP fetching domain, as it might lack coverage for specialized scenarios like WebSocket handling or advanced caching. However, the tools cover core use cases (dynamic page scraping and generic HTTP requests), making it borderline but functional.

Completeness4/5

The tool set covers essential HTTP operations for web scraping and API interactions, with clear guidance on when to use each tool. Minor gaps exist, such as no dedicated tools for WebSocket connections or batch request handling, but agents can likely work around these using the provided tools.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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