Buy timestamped web, company, commerce, social, document and decision data via x402.
Validate a selected capability input and begin execution. Returns the exact paid HTTP request; an unpaid request to that URL returns the x402 challenge, and a paid request returns the result.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | ||
| capabilityId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond the readOnlyHint annotation by explaining the x402 payment mechanism and what happens with unpaid vs paid requests. This is critical for the agent to understand side effects and expectations.
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?
Two sentences efficiently convey the purpose and the unique payment behavior. No redundant information. The description is front-loaded with the main 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?
The description explains the return behavior (paid/unpaid request) and the validation step, but omits input semantics and any invocation prerequisites. Given the absence of an output schema, the description does a good job for the core execution flow, but parameter details are 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?
The description provides no detail about the parameters. The input schema has 0% coverage, and the description doesn't explain what 'input' should contain or how it relates to the capabilityId. The enum itself is documented in the schema, but the generic 'input' object is left completely undefined.
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's function: validate a capability input and begin execution. It also explicitly explains the paid/unpaid request behavior, distinguishing it from sibling search_capabilities which is for searching.
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 you have a 'selected capability', and the sibling tool search_capabilities exists for discovery. It doesn't explicitly mention when not to use or alternative tools, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Free. Find live source-backed capabilities and their exact x402 prices for a goal.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description is not required to restate. It adds valuable context beyond annotations: 'Free' indicates cost, 'live source-backed' implies real-time data freshness, and 'exact x402 prices' highlights precision. No contradiction 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, front-loaded with the cost ('Free') and then the core action. Every word contributes, with no filler or redundancy.
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 tool with only one optional parameter and no output schema, the description covers the essential behavior, cost, and data freshness. It does not explicitly describe the return format, but the action 'find capabilities and their prices' implies a list of matches. Minor gap: no mention of limits or pagination.
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 0%, so the description must compensate. It provides some semantic hint: 'for a goal' suggests the 'query' parameter is the goal to search for. However, no details are given on format, examples, or optionality, leaving the parameter meaning partially under-specified.
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?
Description clearly states the tool's function: 'Find live source-backed capabilities and their exact x402 prices for a goal.' The verb 'find' and resource 'capabilities' are specific and distinguish this from the sibling 'execute_capability' tool.
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 phrase 'for a goal' implies the user should provide a goal to search, but there is no explicit guidance on when to use this over the sibling tool, nor any exclusions. Usage context is inferred rather than clearly stated.
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.
execute_capabilitysearch_capabilitiesClaiming 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.
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Pay-per-call government data over x402: provenance chains, Ed25519 attestations, no API keys.
Bounded data, document, web-quality, and operations services purchased with USDC through x402.
Pay-per-use AI and data tools via x402: image, video, music, voice, search, crypto. USDC.
x402-paid analytics, market intelligence, research, and LLM inference for AI agents.
Add one secure layer between your agents and this server.
The two tools have clearly distinct purposes: one for discovering capabilities and their prices, and one for executing a selected capability. There is no overlap or ambiguity between them.
Both tool names follow a consistent verb_noun pattern (execute_capability, search_capabilities), with only a negligible singular/plural difference that does not affect clarity or predictability.
With only two tools, the set is minimal and sits at the borderline of what feels appropriate. For such a focused domain it may be sufficient, but it is on the thin side compared to typical well-scoped servers.
The server covers the complete workflow of discovering and executing paid capabilities, from search to execution. There are no obvious missing operations for its narrow scope.
