Remote MCP
Server Details
The Remote MCP server acts as a standardized bridge between LLM applications (like Claude, ChatGPT, and Cursor) and external services, enabling AI agents to access external tools and resources. Its primary capability is providing a centralized search tool to discover other MCP servers and their respective tools. Unlike local implementations, it runs remotely with OAuth authentication and permission controls for security.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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 3.3/5 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 as listing and searching for trusted Remote MCP Servers from specific sources.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'ListRemoteMCPServers' follows a clear verb_noun pattern, making it predictable and readable.
A single tool is too few for a server named 'Remote MCP', which implies broader functionality for managing remote servers. This minimal toolset feels thin and under-scoped for the apparent domain, limiting agent capabilities.
The tool surface is severely incomplete for the inferred domain of remote MCP server management. While listing servers is covered, there are significant gaps such as adding, removing, configuring, or interacting with servers, which are essential operations for this purpose.
Available Tools
1 toolListRemoteMCPServersBRead-onlyIdempotentInspect
List and search for trusted Remote MCP Servers from https://github.com/jaw9c/awesome-remote-mcp-servers and https://remote-mcp.com
| Name | Required | Description | Default |
|---|---|---|---|
| query | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations cover key behavioral traits: readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, indicating a safe, non-destructive, repeatable operation with a closed set of data. The description adds context by specifying the data sources (GitHub and remote-mcp.com), which is useful beyond annotations. However, it doesn't disclose additional behaviors like rate limits, authentication needs, or response format, keeping the score moderate.
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, efficient sentence that front-loads the core purpose ('List and search for trusted Remote MCP Servers') and includes essential sources without unnecessary details. Every word contributes to understanding the tool's scope, making it highly concise and well-structured.
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 low complexity (one parameter, no output schema) and rich annotations (covering safety and idempotency), the description is adequate but has gaps. It specifies data sources but doesn't explain the query parameter or return values. For a search tool, more details on usage or results would improve completeness, but annotations provide sufficient behavioral context to avoid a lower score.
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 input schema has one parameter ('query') with 0% description coverage, meaning the schema provides no details about it. The description mentions 'search' but doesn't explain what the query parameter does, its format, or examples. It adds minimal semantic value beyond the schema, so it meets the baseline score of 3 for low coverage without compensation.
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: 'List and search for trusted Remote MCP Servers' with specific sources mentioned (GitHub and remote-mcp.com). It uses the verb 'list and search' and identifies the resource as 'trusted Remote MCP Servers,' making the action and target explicit. However, since there are no sibling tools, it doesn't need to differentiate from alternatives, so it doesn't reach the highest score of 5.
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 no guidance on when to use this tool versus alternatives, prerequisites, or exclusions. It simply states what the tool does without context for its application. Since there are no sibling tools, the lack of differentiation is not penalized, but overall usage guidance is absent.
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.
Discussions
No comments yet. Be the first to start the discussion!