Skip to main content
Glama
Sign In
LemonMCP

LemonMCP

Official
by lemonXGroup
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_captured_request

Fetch full HTTP request and response data for a specific captured transaction using its trace_id, transaction_id, or legacy database id.

Instructions

Reads one complete captured request/response by transaction_id, trace_id, or the legacy database id returned by search_traffic_previews. Body metadata distinguishes missing, empty, text, and binary-file payloads.

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": {
      "trace_id": "<trace_id>"
    },
    "name": "get_captured_request"
  }
}

Input Schema

NameRequiredDescriptionDefault
trace_idYesStable request identifier returned as trace_id by search_traffic_previews.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose a genuinely useful behavioral trait — that body metadata distinguishes missing, empty, text, and binary-file payloads, hinting that binary content is not inlined — but it says nothing about permissions, size limits, or failure modes when an id is stale.

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?

A single dense sentence, front-loaded with the verb and resource, with no wasted clauses. It is slightly overpacked by enumerating three identifier types that the schema does not support.

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?

With no output schema, the description should explain what comes back; it only gestures at body metadata categories and leaves the response shape otherwise unspecified. For a detail-fetch tool this is adequate-but-thin, and the identifier mismatch with the schema is left unresolved.

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% for the single trace_id parameter, so the baseline is 3. The description's claim that transaction_id and a legacy database id also work is not reflected in the schema, which adds ambiguity rather than meaning.

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

Purpose4/5

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

States a specific verb (reads) and resource (one complete captured request/response) plus the lookup keys, and its sibling search_traffic_previews is named as the source of identifiers, so an agent can tell the preview-list tool from the full-detail tool. The only wrinkle is that it advertises three key types (transaction_id, trace_id, legacy database id) while the schema accepts only trace_id.

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 reference to search_traffic_previews implies this is the follow-up call when you need full bodies rather than preview listings, but there is no explicit when-to-use/when-not statement or exclusion. Usage is inferable rather than stated.

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

Deploy Server

Other Tools