nohumans.directory
Server Details
Curated, probe-verified directory of paid x402 APIs. Agents check it before spending money.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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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.
Tool Definition Quality
Average 4.5/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: one searches for services, the other retrieves details for a specific service. No overlap in functionality.
Both tool names follow a consistent verb_noun pattern (find_paid_service, get_service_details), using snake_case throughout.
Only 2 tools feels thin for a directory, even a specialized one. While the purpose is narrow, a listing or category tool could be expected.
The tools cover search and details for paid services, but there is no way to list all services, filter by criteria like chain, or submit new listings. Notable gaps exist.
Available Tools
2 toolsfind_paid_serviceAInspect
Search a verified registry of paid (x402) APIs and datasets. Returns ranked results: verified listings first, then by reputation score (0..1, recency-weighted probe success), then by ascending price. Use this before spending money to find services that actually work. Prefer results with status 'verified' and score >= 0.8. Zero results means no known service matches — do not invent endpoints.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum results to return (default 10, cap 50). | |
| query | No | Free-text search matched against service names and descriptions, e.g. 'fx rates', 'translation', 'weather'. Omit to browse. | |
| category | No | Exact category filter, dot-namespaced, e.g. 'data.fx', 'compute.translation'. | |
| max_price | No | Maximum per-call price. Omit for no cap. | |
| min_score | No | Minimum reputation score, 0..1. Use 0.8 to only see reliably-passing services. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the ranking order (verified first, then reputation score, then price), but does not mention read-only nature, authentication, or rate limits. The description is still informative, but could be more 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 four sentences long, each serving a distinct purpose: stating the tool's function, explaining ranking, giving usage advice, and handling edge cases. No redundant information.
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 no output schema, the description could be more complete by listing return fields, but it does cover ranking, status filtering, and score thresholds. It feels sufficient for an agent to use the tool correctly.
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% meaning the schema already describes each parameter. The description adds value by explaining ranking logic and score interpretation, but does not add significant new meaning for individual parameters beyond the schema.
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 verb 'Search' and the resource 'verified registry of paid (x402) APIs and datasets'. It distinguishes itself from the sibling tool 'get_service_details' by focusing on searching rather than retrieving details.
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?
Provides explicit guidance: 'Use this before spending money to find services that actually work.' Also advises preferring verified listings with score >= 0.8 and warns not to invent endpoints when zero results, which sets clear expectations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_service_detailsAInspect
Fetch the full record for one listing by id (from find_paid_service results): endpoint URL, request/response JSON Schemas when provided, accepted chains, pricing, and reputation detail (probe count, last successful probe, consecutive failures). Call this before making a paid request so you know the exact request shape and current reliability.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Listing id, as returned by find_paid_service. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description details what the tool returns (including reputation metrics like probe count, last successful probe, consecutive failures) and implies it is a read operation with no side effects. The mention of 'current reliability' indicates timeliness.
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, front-loaded with purpose and contents, followed by usage guidance. No wasted words; every sentence is necessary and informative.
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 one parameter and no output schema, the description thoroughly explains what the tool returns (endpoint URL, schemas, chains, pricing, reputation). It provides sufficient context for an agent to understand the tool's value and output.
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 has 100% coverage with one parameter 'id' described as 'Listing id, as returned by find_paid_service.' The description adds value by explaining the origin and purpose of the id, going beyond the schema.
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 it fetches the full record for a listing by ID, enumerating specific fields (endpoint URL, request/response JSON Schemas, accepted chains, pricing, reputation). It distinguishes itself from the sibling find_paid_service by its purpose.
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?
Explicitly states when to use: 'Call this before making a paid request so you know the exact request shape and current reliability.' Does not specify when not to use or mention alternatives, but provides clear context.
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
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