Buy timestamped web, company, commerce, social, document and decision data via x402.
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Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4.2/5 across 2 of 2 tools scored.
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.
execute_capabilityExecute an Agent Reality capabilityAValidate 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.
search_capabilitiesSearch Agent Reality capabilitiesAFree. 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.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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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
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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
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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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