Go MCP server for GitLab: 2 dynamic tools reach 1000+ REST/GraphQL actions. Free/CE, no paid tier.
Execute one GitLab catalog action by canonical ID or alias. Always pass params as an object. Destructive actions require top-level confirm=true. Use find first only when action or params are unclear.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | Canonical action ID returned by gitlab_find_action, or a supported compatibility alias, such as project.list, issue.update, or issue.close. | |
| params | Yes | Required action-specific parameters object validated by the selected action schema. Use an empty object for actions with no parameters. | |
| confirm | No | Set top-level confirm=true to explicitly approve destructive actions. Do not put confirm inside params for gitlab_execute_action. |
| Name | Required | Description |
|---|---|---|
| next_steps | No | Optional. Suggested follow-up actions or tool calls for the LLM, contextual to the result. |
| pagination | No | Present on list actions. Use `has_more` and `next_page` to paginate through results. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true and readOnlyHint=false, but the description adds an important behavioral requirement: destructive actions require top-level confirm=true. It also signals that the tool is general-purpose by saying 'one GitLab catalog action,' which helps set expectations versus a specialized tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences: the first states the core function, the second gives a required parameter convention, and the third gives the key safety and routing rule. Every sentence contributes new, actionable information with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a generic action-executor with an open-world catalog, the description provides full operational context: how to identify actions, how to pass parameters, how to handle destructive actions, and when to fall back to the sibling discovery tool. The output schema covers return-value expectations, so nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents action, params, and confirm with clear descriptions. The description mostly restates these constraints ('Always pass params as an object', confirm requirement) rather than adding new parameter semantics, but it does reinforce the canonical-vs-alias action concept.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Execute one GitLab catalog action by canonical ID or alias.' It also names the sibling relationship indirectly by saying to use find first when actions are unclear, which distinguishes this execution tool from gitlab_find_action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage rules: pass params as an object, set top-level confirm=true for destructive actions, and use find first only when action or params are unclear. This gives an agent clear decision criteria for when to call this tool versus gitlab_find_action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the local GitLab action catalog. Read-only and no GitLab API call. Use when the action ID or params are unclear. Returns schemas, hints, destructive flags, and execute examples.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of matches to return. Defaults to 20 and is capped at 50. | |
| query | Yes | Search terms combining a GitLab domain or resource with a verb, filter, or object name, such as project create, merge request approve, pipeline retry, issue delete, or ci variable. | |
| explain | No | When true, include deterministic scoring reasons for each returned action. Defaults to false to keep responses compact. |
| Name | Required | Description |
|---|---|---|
| count | Yes | Number of returned matches. |
| query | Yes | Original search query. |
| results | Yes | Matching GitLab catalog actions with schemas and execute examples. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations by clarifying that this is a local catalog search with no GitLab API call, and by enumerating what the response includes. This meaningfully supplements the structured metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four short sentences, each earning its place: what it does, side effects or lack of API call, when to use it, and what it returns. It is front-loaded with the primary purpose and avoids redundant detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the rich annotations, full schema coverage, and presence of an output schema, the description is complete. It tells an agent enough to select the tool and invoke it correctly, including its local non-API nature and what kind of results to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameter descriptions already fully document the query, limit, and explain parameters. The tool description does not add parameter-level meaning beyond this, which fits the baseline of 3 when the schema carries the burden.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Search') and resource ('local GitLab action catalog'), clearly distinguishing it from gitlab_execute_action by noting it is read-only and makes no API call. It explains exactly what the tool does without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool: 'Use when the action ID or params are unclear.' It provides clear context but does not explicitly mention the sibling tool or state when not to use it, so it stops short of full exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
gitlab_execute_actiongitlab_find_actionClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
GitLab MCP — wraps the GitLab REST API v4 (BYO API key)
GitLab Public MCP — wraps the GitLab REST API v4 (public endpoints, no auth)
A MCP server built for developers enabling Git based project management with project and personal…
Add one secure layer between your agents and this server.
Each tool has a clearly distinct role: one locates/describes catalog actions, the other executes them. There is no overlap in purpose or behavior.
Both tools follow the gitlab_verb_noun pattern with consistent snake_case, and the action/find_action verbs clearly indicate their operations.
Two tools is below the typical well-scoped range, but the design intentionally uses a catalog dispatcher rather than individual endpoints. It feels minimal yet justified; a third tool for listing catalog contents directly would round it out.
The execute_action tool effectively covers any GitLab operation available in the catalog, so there are no obvious missing actions. The only minor gap is agent reliance on discovery through find_action since no direct listing/search-by-entity surface exists.
