A semantic search server that gives AI assistants instant access to Dodo Payments documentation and knowledge base.
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Average 4/5 across 1 of 1 tools scored.
Only one tool exists, so there is no possibility of confusion between tools. The purpose is clearly defined.
The single tool name 'search_docs' follows a clear verb_noun pattern, consistent with best practices.
With only one tool, the server feels too thin for a knowledge MCP, even if search is the core function. A documentation server typically benefits from additional tools like get_doc or list_topics.
Search alone covers the primary use case, but the absence of direct retrieval or listing capabilities leaves notable gaps. Agents must rely entirely on search results without a way to fetch full documents or explore topics systematically.
search_docsSearch Dodo Payments DocumentationAInspectSearch the Dodo Payments documentation using semantic search across API Reference, SDK docs, BillingSDK, and guides.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results to return (default: 10, max: 20) | |
| query | Yes | Search query - describe what you want to find in the documentation. Be specific and mention the framework/language or any other relevant information in query for precise retrieval |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden. It does disclose that the tool uses 'semantic search,' which is a behavioral trait, and mentions the coverage areas. However, it omits other useful behavior details such as result format, pagination, or any potential side effects (though search tools are inherently read-only). The transparency is adequate but not rich.
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, well-structured sentence that front-loads the primary verb and resource. It includes all necessary information (semantic search and the doc domains) without any unnecessary words or repetition.
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 search tool with two well-documented parameters and no output schema, the description is quite complete. It tells the agent exactly what is searched and how. The only minor gap is the lack of detail about the return structure, but given the low complexity and read-only nature, the description suffices.
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 schema provides 100% coverage for the two parameters (query and limit), including descriptions and constraints. The tool description adds no additional parameter semantics beyond what the schema already states, such as the guidance to be specific in the query. Thus, the 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's purpose: to search Dodo Payments documentation via semantic search across specific doc areas (API Reference, SDK docs, BillingSDK, and guides). The verb 'search' and resource 'Dodo Payments documentation' are explicit and unambiguous, making it distinct from any potential sibling tools.
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 provides clear context for when to use this tool: whenever the user needs to find information in the Dodo Payments documentation. It lists the exact scopes (API Reference, SDK docs, etc.), so an agent can infer its applicability. No explicit exclusions or alternative tools are mentioned, but the context is sufficiently clear.
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
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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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