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gitflic-mcp

gitflic-mcp

by revenant20
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

list_mr_discussions

List paginated merge request discussion threads with author, message preview, and resolved status for general and code-line comments. Use for an overview before fetching full details.

Instructions

List discussion threads on a merge request with pagination. Returns discussion UUID, author, message preview, and resolved status. Discussions can be general comments or line-level code comments. Use get_mr_discussion for full thread details.

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>",
      "project": "<project>",
      "mr_id": "<mr_id>"
    },
    "name": "list_mr_discussions"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageNoPage number (0-based)
sizeNoItems per page
mr_idYesMerge request local ID
ownerYesProject owner alias
projectYesProject alias

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden. It discloses return fields (UUID, author, message preview, resolved status) and clarifies that discussions can be general or line-level comments. This goes beyond a simple 'list' and gives useful behavioral context, though it does not mention access requirements or error 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 three concise sentences with no fluff. It opens with the core purpose, then lists return values, and ends with a useful sibling pointer—each sentence earns its place.

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?

Given there is no output schema, the description helpfully specifies the return fields. It also covers pagination and the two types of discussions. It does not mention default page/size or edge cases, but for a simple list tool with a well-explained schema, this is largely sufficient.

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 schema already documents all parameters. The description mentions pagination, which partly relates to the page/size parameters, but adds no extra parameter-specific meaning beyond the schema.

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 uses a specific verb ('List') and resource ('discussion threads on a merge request') with clear scope and pagination. It explicitly differentiates from the sibling tool get_mr_discussion by noting that the latter provides full thread details.

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

Usage Guidelines5/5

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

The description explicitly states an alternative: 'Use get_mr_discussion for full thread details.' This implies that this tool is for summary/listing when full details are not needed, providing clear when-to-use versus when-not-to-use guidance.

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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