oathlayer
Server Details
Verify AI outputs against real sources. Returns a trust signal and permanent doc number.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- oathlayer/oathlayer
- GitHub Stars
- 0
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Usage analytics
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Tool Definition Quality
Average 3.8/5 across 1 of 1 tools scored.
With only one tool, there is no possibility of confusion. The tool's purpose is clearly defined and distinct.
The tool name 'verify_output' follows a clear verb_noun pattern. Consistency is not an issue with a single tool.
A single tool is appropriate for a specialized verification service, though the scope is very narrow and slightly below typical range.
The tool covers the core verification operation but lacks additional features like retrieval or history, which could be considered minor gaps.
Available Tools
1 toolverify_outputAInspect
Submit a question to Oathlayer for verification. Returns whether the answer is approved, unverified, reflects multiple perspectives, is too complex to verify, or needs clarification. Also returns a permanent doc reference number.
| Name | Required | Description | Default |
|---|---|---|---|
| apiKey | Yes | Your Oathlayer API key from your dashboard at oathlayer.com. | |
| question | Yes | The question or statement you want Oathlayer to verify. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden. It discloses return values (statuses and doc reference) but does not state side effects, authentication needs beyond the apiKey, or rate limits.
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 concise sentences front-load the action and then detail returned values, with 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?
For a simple two-parameter tool with no output schema, the description adequately covers functionality and return values. Minor gap: no mention of idempotency or side effects.
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?
100% schema coverage means the schema already describes parameters. Description adds no new semantic meaning beyond listing the same information.
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 'submit' and the resource 'question to Oathlayer', and lists specific return statuses, making its purpose unambiguous.
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?
No explicit when-to-use or when-not-to-use guidance is provided. Usage is implied but no alternatives or context are given.
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
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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