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Tls Fetch

tls_fetch

Fetches raw HTTP responses with Chrome TLS fingerprints, skipping browser rendering when you only need JSON or HTML from APIs and static pages.

Instructions

Raw HTTP w/ Chrome JA3+JA4. Skip DOM when you only need JSON/HTML. ~50ms vs ~500ms. Skip on client-side-rendered SPAs. Needs pip install umbra-browser[tls].

Ex: tls_fetch('https://api.example.com/users') → {"status":200,"headers":{...},"body":"{"users":[...]}"}

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "tls_fetch"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYes
bodyNo
methodNoGET
headersNo
max_charsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries full behavioral burden: it discloses the JA3/JA4 fingerprinting, the ~50ms vs ~500ms performance delta, no-DOM behavior, and the extra dependency. However, it omits important traits — a method parameter defaulting to GET plus an optional body means this can issue non-GET requests (potentially mutating), and nothing is said about redirects, cookies, auth headers, or that max_chars truncates the response body.

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?

Very short and front-loaded with the differentiator and the exclusions first, then the example. The telegraphic fragments ('Raw HTTP w/ Chrome JA3+JA4') are efficient but slightly terse, and the example adds little beyond the output schema.

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

Completeness3/5

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

The output schema covers the return shape, so the example return value is redundant rather than necessary. Combined with zero-coverage parameter schema and undisclosed POST/body capability, an agent can figure out the happy path but not the full calling contract.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for all five parameters, yet it only demonstrates the url argument in the example. method, headers, body, and especially max_chars (default 8000, which silently truncates output) are undocumented anywhere.

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?

'Raw HTTP w/ Chrome JA3+JA4' names the specific mechanism (raw HTTP request with Chrome TLS fingerprint) rather than a vague verb. The 'Skip DOM when you only need JSON/HTML' line clearly separates it from the browser-rendering siblings like navigate, extract_text, and extract_markdown.

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?

It gives both sides explicitly: use it when you only need JSON/HTML without a DOM, and skip it for client-side-rendered SPAs where navigate/render siblings are needed. It also states the concrete precondition 'Needs pip install umbra-browser[tls]', which prevents a predictable failure mode.

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