ELSA — Coach IA de ciclismo y comunidad en LATAM: planifica tu bloque y encuentra tu club.
Recomienda el club de ELSA que mejor calza con tu volumen y zona, y te lleva a unirte y confirmar tu primer evento.
| Name | Required | Description | Default |
|---|---|---|---|
| location | Yes | City or area | |
| preferred_days | No | ||
| weekly_volume_km | Yes | Typical weekly volume in km |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates a write operation ('te lleva a unirte y confirmar tu primer evento'), but the annotations declare readOnlyHint: true. This is a direct contradiction, severely undermining transparency. The description should align with the annotation or clarify the join flow as a separate action.
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 a single sentence with 150 characters, front-loading the verb 'recommend'. It is efficient but could benefit from breaking into clearer components (e.g., recommendation, then join action).
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?
With 3 params, no output schema, and a contradictory annotation, the description leaves gaps: it does not explain how preferred_days is used, what the output looks like, or resolve the read/write inconsistency. The join process is mentioned but not clarified that it may involve external navigation.
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 67%, with descriptions for location and weekly_volume_km. The description mentions 'volume and zone' mapping to these params, but adds no new detail for preferred_days. It provides marginal additional meaning but does not fully compensate for the missing schema description.
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 states the tool recommends an ELSA club based on volume and area, and guides the user to join and confirm their first event. It uses specific verbs and resource, and differentiates from sibling tool plan_my_block which likely handles planning blocks rather than club matching.
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 implies usage when a user wants a club recommendation but provides no explicit guidance on when to use this tool versus the sibling tool plan_my_block. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Devuelve un bloque de entrenamiento ciclista periodizado (base/build/peak/taper) hacia tu evento meta, con veredicto de readiness, y te lleva a activarlo en ELSA.
| Name | Required | Description | Default |
|---|---|---|---|
| event_date | Yes | ISO date of the goal event | |
| goal_event | Yes | Target event, e.g. 'Gran Fondo 120km' | |
| recent_training | No | Free-text or pasted Garmin/Strava summary |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, indicating no side effects. The description adds that the tool 'te lleva a activarlo en ELSA' (leads to activation), which could be interpreted as a read-only redirection. No hidden side effects are apparent, and the description is consistent with annotations.
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 a single sentence that conveys the key points efficiently. While it could be slightly more concise or broken into two sentences, it avoids unnecessary fluff and is well-structured.
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 tool's complexity (3 parameters, no output schema), the description sufficiently explains the main purpose and return value (periodized block with readiness verdict). However, it lacks details on the exact output format or how the activation step works, which would be helpful for the agent.
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 schema already documents all three parameters. The description does not add new semantic information beyond the purpose, so a baseline score of 3 is appropriate.
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 states the tool returns a periodized cycling training block (base/build/peak/taper) for a goal event, with a readiness verdict. It distinguishes from sibling 'match_me_a_club' which is about club matching.
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 implies usage for planning a training block towards a specific event. While it doesn't explicitly state when not to use it or list alternatives, the sibling tool is very different, making the context clear.
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.
match_me_a_clubplan_my_blockClaiming 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!
AI cycling coach: training plans, workouts, nutrition, strength training, Strava, Garmin and Wahoo.
AI cycling coach — training plans and beginner guidance via the Etapa API.
Turn Claude or ChatGPT into a cycling coach that plans your week, grades it, and adapts. Free beta.
AI soigneur for cyclists: Strava ride to an Ien-Vitse-validated nutrition plan + orderable box.
Add one secure layer between your agents and this server.
The two tools have clearly distinct purposes: one recommends a club, the other plans a training block. There is no overlap or ambiguity.
Both tools follow a consistent verb_noun pattern using underscores, making them predictable and easy to understand.
With only 2 tools, the server feels minimal for a 'gateway' concept. It may be appropriate for a very narrow scope but is at the lower bound of reasonable tool counts.
The server covers club matching and training planning, but lacks other lifecycle operations like tracking progress or managing events, leaving notable gaps for a cycling app domain.
