The issue tracker AI coding agents pull work from: atomic claims, dependency-aware dispatch.
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4.8/5 across 1 of 1 tools scored.
There is only one tool, so there is no ambiguity or risk of an agent misselecting between overlapping tools. Its single-purpose role as a setup/bootstrap operation is clearly communicated.
The name `setup_status` follows a clean verb_noun snake_case pattern and clearly describes its purpose. With only one tool, there are no conflicting or inconsistent naming conventions.
One tool is intentionally appropriate for the bootstrap-only state, since the server is not set up yet and all other tools will load later. It is slightly thin as a full server surface, but reasonable for the current stage.
For the setup-phase workflow, `setup_status` covers the complete process: running the CLI, surfacing the approval URL, acting on the result, and asking the user to restart. There are no obvious missing steps within the documented bootstrap flow.
setup_statusAInspectRetasc is not set up in this folder yet, so this is the only tool available and the only one that will work. Call it and follow what it returns. In short: YOU run npx @retasc/cli@latest bind --json in this folder, in the background, having first told your human that a browser is about to open. Post the approve URL it prints to them as a link, act on what it reports back, and when it finishes ask them to restart you so the rest of the tools load. The click and the restart are theirs; everything else is yours.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The schema and annotations are empty, so the description carries the full burden of disclosing behavior. It does this exceptionally well: it tells the agent to run the CLI in the background, warns that a browser will open, states that an approve URL will be printed and must be posted as a link, and explains the handoff/restart responsibility. Safety/operational details, such as which actions belong to the human vs. the agent, are also explicit.
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 dense and action-rich with clear sequencing, and it front-loads the key context (setup not yet done, only tool that works). It loses one point because 'Call it and follow what it returns' is redundant with later sentences ('act on what it reports back'), and 'In short' introduces a detailed explanation that actually starts a rather large summary, which causes in structure. Otherwise every clause earns its place.
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 zero-parameter tool with no output schema/siblings, the description is remarkably complete. It gives the exact shell command, the background running behavior, the human-notification step, the approval-link workflow, what to do with reports, and the restart handoff. An agent is able to execute the whole flow correctly without any additional context.
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?
The input schema has zero parameters, so there are no parameter semantics for the description to add. With a 0-parameter tool, the baseline is 4, and the description fully covers the only 'inputs' that matter: the exact CLI command to run and the operational steps to take. Nothing about parameters is missing.
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 clearly identifies the tool as the sole action available when Retasc is not yet set up, and states exactly what a successful call accomplishes (running the bind CLI, producing an approval URL, and completing setup). It is not a tautology; it gives a specific verb and resource (setup via `npx @retasc/cli@latest bind`). Even with no siblings, any agent reading it will understand why this tool exists and when it applies.
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?
It explicitly states the triggering condition: 'Retasc is not set up in this folder yet, so this is the only tool available and the only one that will work.' This tells the agent exactly when to invoke it. Since there are no sibling tools, the description doesn't need to name alternatives; it still gives unambiguous context and even explains that after restart the rest of the tools load.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claiming 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 or an account that owns the GitHub organization, then choose Claim with GitHub.
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
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!