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http_get

Read-onlyIdempotent

Perform HTTP GET requests to retrieve web content with status, headers, and body. Includes JSON parsing, redirect following, and SSRF protection that blocks private/loopback addresses unless explicitly allowed.

Instructions

Perform an HTTP GET. Returns status, headers, and body. Automatically parses JSON when the server responds with application/json. Follows redirects (each hop re-validated against SSRF rules). Refuses URLs that resolve to private/loopback/link-local addresses unless allow_private_hosts is set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesTarget URL (http:// or https://)
headersNoExtra request headers as a key/value object
retriesNoRetries on 408/425/429/500/502/503/504 with exponential backoff (default 0)
max_bytesNoMax response body size in bytes before the body is truncated (default 5MiB, ceiling 100MiB)
basic_authNoHTTP Basic auth credentials
timeout_msNoRequest timeout in ms (default 10000, max 120000)
user_agentNoUser-Agent override (default identifies as @yawlabs/fetch-mcp)
decode_textNoForce text decoding (true) or binary base64 (false). Defaults to auto — text for text/*, json, xml, etc; binary otherwise.
bearer_tokenNoBearer token sent as Authorization: Bearer <token>
max_redirectsNoMax redirect hops to follow (default 5)
allow_private_hostsNoAllow requests to loopback / private / link-local addresses. SSRF protection is on by default — only flip this when intentionally talking to localhost.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.1

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses important behaviors: automatic JSON parsing for application/json responses, redirect following with per-hop SSRF re-validation, and refusal of private/loopback/link-local addresses unless allow_private_hosts is set. These are non-obvious and genuinely useful.

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?

Three sentences, each earning its place: the action and return value, the JSON parsing behavior, and the redirect/SSRF behavior. Front-loaded, no filler, and appropriately sized for an 11-parameter tool.

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?

The description covers what the tool returns, how it parses responses, how it handles redirects, and the key SSRF safety constraint. Given the detailed input schema and the absence of an output schema, this is complete enough for an agent to call it correctly.

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?

Schema description coverage is 100%, so the baseline of 3 applies. The description does add one parameter-related detail (allow_private_hosts disables SSRF blocking), but it does not systematically enrich the parameter documentation beyond what the schema already provides.

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 states a specific verb and resource: 'Perform an HTTP GET. Returns status, headers, and body.' This clearly distinguishes it from HTTP sibling methods (post/put/patch/delete/head/options) and from the specialized fetch_* tools, which are not raw HTTP GET operations.

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

Usage Guidelines3/5

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

The context is clear: use this tool for raw HTTP GET requests. However, it never explicitly mentions when to prefer a sibling like fetch_reader or fetch_html_to_markdown, nor does it state when not to use it. Usage is implied by the name and description rather than explicitly contrasted with alternatives.

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