Gitlab MCP Server
Server Quality Checklist
Latest release: v2.7.5
- Disambiguation5/5
gitlab_execute_action and gitlab_find_action have clearly distinct responsibilities: one runs a catalog action, the other searches for catalog information. There is no functional overlap or ambiguity between them.
Naming Consistency5/5Both tools use the same gitlab_<verb>_action pattern in snake_case. The verb-noun structure is consistent and predictable.
Tool Count4/5Two tools is slightly below the typical 3-15 range, but the split between finding and executing actions is a reasonable minimal surface for a catalog-driven server. It feels compact rather than incomplete.
Completeness5/5The pair forms a complete discover-and-execute workflow: find_action provides schemas and execution examples, and execute_action performs the requested catalog action. Since execution is generic, the tool surface itself has no dead ends.
Average 4.4/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 3 of 4 community issues answered or closed in the last 6 months
- 223 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
This server has been verified by its author.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable context beyond annotations: it searches a local catalog rather than making an external GitLab API call, and it returns schemas, hints, destructive flags, and execute examples.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two tightly written sentences. The primary purpose and key behavioral distinction are front-loaded, followed by the intended use case and return contents. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only search tool with fully documented parameters, strong annotations, and an output schema, the description covers the essential use case, behavior, and return value expectations. Nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are already well documented. The description reinforces that the query is a search against the local catalog but does not need to add further parameter detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Search the local GitLab action catalog.' It is clearly distinguished from the sibling execution tool by noting it performs no GitLab API call and is read-only.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use when 'the action ID or params are unclear,' giving a clear trigger condition. It does not name the sibling alternative directly, but the read-only/no-API-call contrast with gitlab_execute_action makes the intended usage evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already indicate destructiveHint=true, readOnlyHint=false, and idempotentHint=false. The description adds meaningful behavioral context beyond those hints by specifying that destructive actions require top-level confirm=true, which is essential for safe invocation of this dynamic executor.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences with no wasted words. It front-loads the core purpose, follows with the most critical invocation constraints, and ends with a clear routing instruction for the sibling tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists and the annotations cover read-only, idempotency, and destructive behavior, the description provides the remaining key context: how to invoke the action, when confirmation is required, and when to defer to gitlab_find_action. Nothing essential is missing for an agent to use this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 three parameters well. The description reinforces the top-level confirm rule and the object-shaped params requirement, but it mostly restates what the schema already provides, so the added semantic value is limited.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action: 'Execute one GitLab catalog action by canonical ID or alias.' This clearly identifies what the tool does and distinguishes it from the sibling tool gitlab_find_action, which is about discovery rather than execution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage routing: 'Use find first only when action or params are unclear.' It also provides concrete invocation guidance, such as always passing params as an object and using top-level confirm=true for destructive actions, which helps the agent call it correctly.
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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- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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