GitLab MCP Server

list_merge_requests

List merge requests in a GitLab project. Filter by state, target or source branch, and search terms to find specific merge requests efficiently.

Instructions

List merge requests in a GitLab project.

Args: project_path: Full path of the project (e.g., 'group/project') state: Filter by state: 'opened', 'closed', 'merged', or 'all' target_branch: Filter by target branch name source_branch: Filter by source branch name search: Search term to filter merge requests per_page: Number of results per page (max 100)

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": {
      "project_path": "<project_path>"
    },
    "name": "list_merge_requests"
  }
}

Input Schema

Name	Required	Default
`state`	No	opened
`search`	No
`per_page`	No
`project_path`	Yes
`source_branch`	No
`target_branch`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 6, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the burden. It explains parameters but does not disclose behavioral traits such as read-only nature, pagination behavior, required permissions, or rate limits. The per_page parameter hints at pagination but no details.

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?

The description is concise and structured with an Args section listing parameters. It is front-loaded with the main purpose. Slight wordiness in parameter descriptions could be trimmed, but overall efficient.

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 list tool with 6 parameters and an output schema, the description covers parameter semantics well. It lacks details on ordering or pagination beyond per_page, but the output schema likely handles return structure. Not fully complete but adequate.

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 description coverage is 0%, so the description fully compensates by explaining each parameter's purpose and expected values (e.g., 'state: Filter by state: opened, closed, merged, or all'). This adds critical meaning beyond the schema's type and default.

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 clearly states 'List merge requests in a GitLab project', using a specific verb and resource. It distinguishes from sibling tools like 'get_merge_request' (single) and 'my_merge_requests' (personal list) through the project_path requirement and filtering options.

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 description implies usage for listing all MRs in a project with various filters, but does not explicitly state when to use this tool over alternatives like 'my_merge_requests' or 'team_merge_requests'. No when-not or exclusion criteria are provided.

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