GitHub Assistant MCP Server

list_issues

List bugs, feature requests, and tasks in a GitHub repository, with optional filters for issue state and result count.

Instructions

List issues for a GitHub repository.

Use this when the user wants to see what bugs, feature requests, or tasks are open in a project — e.g. "what issues are open in pallets/flask?", "show me recently updated closed issues in django/django".

Args: owner: Repository owner (GitHub username or organisation). repo: Repository name. state: Filter by issue state: "open" (default), "closed", or "all". limit: Max number of issues to return (1-50, default 20).

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": {
      "owner": "<owner>",
      "repo": "<repo>"
    },
    "name": "list_issues"
  }
}

Input Schema

Name	Required	Default
`repo`	Yes
`limit`	No
`owner`	Yes
`state`	No	open

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 30, 2026

TDQS

A4.3/5.0

Behavior3/5

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

There are no annotations, so the description carries the full burden, but it only states the list behavior and parameter defaults. It does not mention authentication, ordering, whether pull requests are included in issue results, or other non-obvious API behavior.

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 compact and front-loaded: one sentence says what it does, another says when to use it with two examples, then a clear Args block follows. There is no filler or repetition.

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?

For a simple list endpoint with an output schema, the description covers the core invocation requirements. It could be more complete by noting GitHub API quirks like the issues endpoint also returning pull requests, but that is an edge case.

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

Parameters5/5

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

Schema descriptions are absent (0% coverage), and the Args section fully compensates: owner is defined as a GitHub username/organisation, state lists its allowed values and default, and limit gets its numeric range and default. This provides exactly the meaning an agent needs beyond bare schema types.

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 opens with 'List issues for a GitHub repository,' a specific verb and resource that clearly separates it from siblings like get_issue and list_pull_requests. The examples ('bugs, feature requests, or tasks') reinforce that this targets issue lists rather than repositories or PRs.

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

Usage Guidelines4/5

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

'Use this when the user wants to see what bugs, feature requests, or tasks are open' gives explicit triggering scenarios with concrete examples. It does not name alternatives or state when not to use it, so it stops short of a 5.

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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