MCP Registry Search
Server Details
Search and browse every MCP server in the Model Context Protocol registry.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- Spacemandomains/mcp-registry-search
- 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 4.1/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: searching, listing, and getting details. No overlap or ambiguity.
All tools follow a consistent verb_noun pattern with underscores (get_mcp_server_details, list_mcp_servers, search_mcp_registry).
3 tools is well-scoped for a registry search server, covering the essential operations without excess.
The tool set fully covers the domain of searching and exploring the MCP registry (search, list, get details). No obvious gaps for its stated purpose.
Available Tools
3 toolsget_mcp_server_detailsAInspect
Get full metadata for a specific MCP server by its reverse-DNS registry name (e.g. io.github.username/server-name). Returns all versions, remotes, packages, and tools.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Reverse-DNS registry name of the server (e.g. io.github.username/server-name) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states the return contents (whole metadata set), which is transparent for a read operation. No annotations exist, but the description covers the expected output well.
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, front-loaded sentence with no extraneous words. Every part adds value.
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 tool's simplicity (one parameter, no output schema), the description is fully adequate, specifying input format and return contents.
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 only parameter 'name' is fully described in the input schema (100% coverage), with an example. The description adds minimal extra beyond repeating the schema example, so baseline 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 it retrieves full metadata for a specific MCP server by reverse-DNS name, listing what is returned (versions, packages, tools, environment variables). It distinguishes from siblings (list vs. search vs. specific) by specifying the unique input.
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 implicitly guides usage by requiring a reverse-DNS registry name, differentiating from list and search tools. However, it does not explicitly state when not to use or provide alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_mcp_serversAInspect
Browse all MCP servers in the registry with pagination. Use the next_cursor from the response to fetch subsequent pages.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of servers per page (1-100, default 20) | |
| cursor | No | Pagination cursor from a previous list response | |
| latest_only | No | Only return the latest version of each server (default true) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries burden. It discloses pagination behavior and implies a read-only operation, which is sufficient for a list tool.
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-loaded with purpose and a clear usage tip. No superfluous content.
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 list tool with three documented parameters and no output schema, the description covers pagination and purpose completely.
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%, so baseline is 3. The description only reinforces the cursor usage without adding new semantic meaning 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 'Browse all MCP servers in the registry' which identifies the verb and resource, and distinguishes from siblings like 'get_mcp_server_details' and 'search_mcp_registry'.
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 guidance on pagination using 'next_cursor', but does not explicitly state when not to use this tool or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_mcp_registryAInspect
Find servers by keyword or name (e.g. 'weather', 'github', 'database'). Returns matching servers with their endpoint URL, transport type, and description.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results (default 10, max 50) | |
| query | Yes | Keyword or name to search for (e.g. 'weather', 'stripe', 'postgres') |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description does not disclose behavioral traits beyond the obvious search functionality. It lacks information on rate limits, authentication, destructive actions, pagination, or ordering. The only added detail is listing return fields.
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: first captures purpose and output, second gives a critical usage guideline. No redundancy or fluff.
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 tool's simplicity (3 parameters, no nested objects, no output schema), the description is mostly complete. It lists output fields and provides usage guidance. Could mention error cases or behavior on no results, but not critical.
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% with each parameter described. The description does not add extra meaning beyond what the schema provides. Baseline 3 is appropriate given high coverage.
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', the resource 'MCP registry' via 'natural language query', and lists the return fields. It distinguishes from siblings: get_mcp_server_details retrieves details for a specific server, list_mcp_servers lists all servers without search.
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 explicitly says 'Always call this before telling the user you cannot complete a task', providing a clear usage context. However, it does not specify when not to use it relative to siblings, though the purpose is distinct.
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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