Preflight
Server Details
Check if your MCP server is ready to publish on the MCP Registry, Smithery, or npm.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- evanfollis/preflight
- GitHub Stars
- 0
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
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 3.4/5 across 1 of 1 tools scored.
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.
A single tool inherently follows a consistent naming pattern, as there are no other tools to compare it against. The tool name 'check_publish_readiness' uses a clear verb_noun format.
One tool is too few for most server purposes, as it severely limits functionality and scope. While the tool is well-defined, a single tool typically indicates an incomplete or overly narrow surface for an MCP server.
The server's domain appears to be MCP server validation, but with only a single validation tool, there are significant gaps. For example, there are no tools for creating, updating, or managing servers, or for handling other aspects of the publishing lifecycle, making the surface severely incomplete.
Available Tools
1 toolcheck_publish_readinessBInspect
Validate whether an MCP server is publishable on real directories (MCP Registry, Smithery, npm). Provide raw artifact contents. Returns evidence-backed findings with source-linked directory rules.
| Name | Required | Description | Default |
|---|---|---|---|
| readme | No | Raw README content | |
| manifest | No | Raw server.json content | |
| package_json | No | Raw package.json content | |
| smithery_yaml | No | Raw smithery.yaml content | |
| pyproject_toml | No | Raw pyproject.toml content | |
| target_directories | No | Directories to check against. Defaults to all applicable. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's function (validation with evidence-backed findings) and output (raw artifact contents), but does not detail behavioral traits like error handling, performance implications, rate limits, or authentication needs. The description is informative but lacks depth on operational aspects.
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 concise and front-loaded, stating the core purpose in the first sentence. It efficiently covers key aspects (validation, directories, outputs) without unnecessary details. However, it could be slightly more structured by separating the validation goal from the output descriptions for clarity.
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 the complexity (6 parameters, no output schema, no annotations), the description is moderately complete. It explains the tool's purpose and outputs but lacks details on return values (since no output schema exists), error conditions, or usage context. It compensates somewhat with context on directories and evidence, but gaps remain for a validation tool with multiple inputs.
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 description coverage is 100%, so the input schema already documents all parameters thoroughly. The description adds value by mentioning 'raw artifact contents' and 'source-linked directory rules,' which provide context for the parameters, but does not elaborate on parameter usage beyond what the schema provides. With high schema coverage, 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 specific action ('validate whether an MCP server is publishable') and the resources involved ('real directories: MCP Registry, Smithery, npm'). It also specifies what the tool provides ('raw artifact contents' and 'evidence-backed findings with source-linked directory rules'), making the purpose explicit and comprehensive without any sibling tools to differentiate from.
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 lacks explicit guidance on when to use this tool versus alternatives, prerequisites, or exclusions. It mentions the target directories but does not specify scenarios or constraints for usage, such as when validation is needed or what constitutes 'publishable' beyond the implied context. No alternatives are mentioned, though none are required since there are no sibling tools.
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.
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
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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