GitHub MCP Server

search_issues

Search GitHub issues and pull requests using queries to find specific items by status, labels, or repository.

Instructions

Search issues and pull requests across GitHub.

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": {
      "query": "<query>"
    },
    "name": "search_issues"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	Search query (e.g. 'bug repo:owner/repo', 'is:open is:issue label:bug')
`sort`	No	Sort by (best-match, comments, reactions, created, updated)	best-match
`order`	No	Sort order (asc, desc)	desc
`per_page`	No	Results per page (max 100)
`page`	No	Page number

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Mar 8, 2026

TDQS

B3.1/5.0

Behavior2/5

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 behavioral disclosure. It states the tool searches across GitHub, implying it's a read-only operation that doesn't modify data, but it doesn't disclose any behavioral traits such as rate limits, authentication requirements, pagination behavior (beyond what's in the schema), error handling, or what the search scope entails (e.g., public vs. private repos). For a search tool with zero annotation coverage, this is a significant gap.

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 extremely concise—a single sentence—and front-loaded with the core purpose. There's no wasted verbiage or redundancy. Every word earns its place, making it easy for an agent to parse quickly.

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?

Given the tool's moderate complexity (5 parameters, search functionality) and the presence of an output schema (which means the description doesn't need to explain return values), the description is minimally adequate. However, with no annotations and incomplete behavioral context, it leaves gaps in understanding the tool's full behavior and usage scenarios. It meets the baseline for a search tool but doesn't excel.

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 description coverage is 100%, with detailed descriptions for all parameters (e.g., query examples, sort options, defaults). The description adds no parameter-specific information beyond what the schema provides. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description, which applies here.

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's purpose: 'Search issues and pull requests across GitHub.' It specifies the verb ('Search') and resources ('issues and pull requests'), and distinguishes it from other search tools like search_code, search_repositories, and search_users by focusing on issues and pull requests. However, it doesn't explicitly differentiate from list_issues, which might be a more specific listing tool, so it's not 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer search_issues over list_issues (which might list issues in a specific repository) or other search tools. There's no context about prerequisites, limitations, or typical use cases, leaving the agent to infer usage from the tool name alone.

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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