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bruno-mcp

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Search Bruno requests

bruno_search_requests

Search API requests across all collections in the workspace using case-insensitive filters for name, path, or URL. Returns matching requests with collection IDs for quick access.

Instructions

Search requests across all collections in the workspace. Returns matching requests with collection id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter by request type (e.g. http or graphql).
queryYesCase-insensitive substring filter for request name, path, and URL.
methodNoFilter by HTTP method (e.g. GET or POST).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.2.0
    • changedInput schema / properties / method / description
      Previous value: -"Filter to requests with this HTTP method (case-insensitive), for example GET or POST."New value: +"Filter by HTTP method (e.g. GET or POST)."
    • changedInput schema / properties / query / description
      Previous value: -"Required case-insensitive substring matched against each request's name, path, and URL."New value: +"Case-insensitive substring filter for request name, path, and URL."
    • changedInput schema / properties / type / description
      Previous value: -"Filter to requests of this type (case-insensitive), for example http or graphql."New value: +"Filter by request type (e.g. http or graphql)."
  2. First observedv0.1.0

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 of disclosing side effects and behavior. It mentions it returns matching requests, implying a read-only operation, but does not explicitly state that it does not modify data or that it is safe to call. The transparency is moderate but not thorough.

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 two sentences, direct, and free of unnecessary detail. It efficiently conveys the tool's purpose and a key aspect of the output, with no fluff or redundancy.

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?

The description provides the essential information needed to invoke the tool: that it searches across all collections and returns matching requests with collection id. Even though there is no output schema, the mention of the return content satisfies basic completeness. It lacks details on pagination or filtering specifics, but these are minor for a search tool.

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?

The schema already provides descriptions for all three parameters: query, type, and method. The tool description does not add any extra context about how these parameters interact or affect the search, so the value added beyond the schema is minimal. Baseline 3 is appropriate.

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?

The description clearly states the tool searches for requests across all collections, using the specific verb 'search' and resource 'requests'. It also mentions it returns matching requests with collection id, which distinguishes it from simply listing requests. However, it does not explicitly contrast with the sibling tool bruno_list_requests, so it stops short of a perfect 5.

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

Usage Guidelines2/5

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

The description says what the tool does but does not explicitly state when to use it over alternatives (e.g., bruno_list_requests or bruno_get_request). There is no guidance about using search when a filter is needed versus listing when a full enumeration is required, leaving the agent to infer usage.

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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