A
license-
qualityB
maintenanceAI-first MCP server discovery tool that enables agents to search, inspect, and install MCP servers from multiple registries.
12
AGPL 3.0
cyanheads-mcp-server
Server Details
Fleet discovery for the cyanheads MCP ecosystem — semantic search + install snippets.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- cyanheads/cyanheads-mcp-server
- GitHub Stars
- 1
- Server Listing
- cyanheads-mcp-server
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MCP client
Glama
MCP server
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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.
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Tool Definition Quality
A4.5/5.0
Tool DescriptionsA
Average 4.5/5 across 2 of 2 tools scored.
Server CoherenceA
Disambiguation5/5
Each tool has a clear, distinct purpose: one searches the catalog, the other retrieves detailed entries. There is no overlap or ambiguity.
Naming Consistency5/5
Both tools follow a consistent snake_case pattern with the server prefix 'cyanheads_' and a verb_noun structure (search_catalog, describe_entry).
Tool Count4/5
With only two tools, the set is minimal but well-suited for a read-only catalog server. A third tool for listing all entries might be beneficial, but the count is otherwise appropriate.
Completeness4/5
The tools cover the essential operations for a catalog: searching and retrieving detailed info. However, missing listing or updating capabilities suggests minor gaps if the catalog is expected to be dynamic.
Available Tools
2 toolscyanheads_describe_entryDescribe Fleet Tool or ServerARead-onlyInspect
Return the description and install snippets for a named tool or server. For tools: the description and the server it belongs to. For servers: local (stdio, via npx) install snippets for every published server, plus remote (HTTP) connection snippets when a hosted endpoint exists — for every supported client, or one client via the client parameter. Call cyanheads_search_catalog first to find valid names.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | Whether name refers to a tool or server. Omit to auto-detect: names containing underscores are treated as tools; names containing hyphens are treated as servers. | |
| name | Yes | Tool name (snake_case, e.g. "earthquake_search") or server name (kebab-case, e.g. "earthquake-mcp-server"). 1-64 characters. Use cyanheads_search_catalog to discover valid names. | |
| client | No | Return install snippets for this client only (both local and remote transports when available). Omit to return snippets for all supported clients. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes | The resolved entry — either a tool detail or a server detail depending on the resolved kind. |
Tool Definition Quality
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and openWorldHint=false, which the description does not contradict. The description adds behavioral context about auto-detection based on naming conventions and the conditional output based on kind and client parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each purposeful. Front-loaded with the core purpose, followed by operational details and a prerequisite. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With three parameters (two with enums), a 100% schema coverage, and an output schema present, the description provides all necessary context: prerequisite search call, conditional output, and client filtering. Complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining the semantics of auto-detection for kind and the effect of the client parameter on output filtering. This goes beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'description and install snippets for a named tool or server' and differentiates behavior between tools and servers. It distinguishes from the sibling tool cyanheads_search_catalog.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly directs users to call cyanheads_search_catalog first to find valid names, providing clear usage context. It also explains the optional kind parameter and auto-detection, but lacks explicit exclusion scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cyanheads_search_catalogSearch Fleet Tools and ServersARead-onlyInspect
Search fleet tools and servers by natural-language description. Returns ranked matches with brief summaries and the server each tool belongs to. Use scope "servers" to find which server handles a workflow; use the default scope "tools" to find specific tools. Call cyanheads_describe_entry on a result name to get install snippets and the connection URL.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return (1-20). Default 5. | |
| query | Yes | Natural language search query. Describe what you want to accomplish, a workflow, or a capability area. 1-500 characters. | |
| scope | No | What to search. "tools" returns individual tool matches; "servers" returns server-level matches. | tools |
| category | No | Filter by catalog category. Omit to search all categories. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| scope | Yes | Scope that was searched. |
| notice | No | Guidance when no results matched — e.g. how to broaden the query or try a different scope. Absent on successful result pages. |
| results | Yes | Ranked matches, best first. |
| servers | No | Roll-up of distinct servers across the full match set, before the limit slice. Present only for scope "tools". Ordered by topScore desc (name-tiebroken); capped at 10. Use serversTotal to see how many distinct servers matched in total. |
| totalCount | Yes | Total relevant matches before the limit was applied. |
| serversTotal | No | Total distinct servers in the full match set (before the cap of 10 is applied). Present only when servers is present. |
| effectiveQuery | Yes | The query that was searched. |
Tool Definition Quality
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, consistent with description. Description adds behavioral context (ranked matches, summaries) beyond annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with all critical information front-loaded. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given annotations, output schema (present), and parameter details, the description covers purpose, usage, and post-use action completely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage; description further clarifies scope usage and output in relation to parameters, adding value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it searches fleet tools/servers by natural-language description, returns ranked matches with summaries and server info. Distinguishes from sibling tool by directing to describe_entry for install details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on using scope 'servers' vs 'tools' and instructs to call describe_entry for install snippets. Lacks explicit 'when not to use' but sufficient for common scenarios.
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
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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
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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