MCP Router
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: add_mcp_server registers servers, exec_mcp_tool executes tools on servers, and search_mcp_server searches for servers. The descriptions reinforce these distinct roles, making misselection unlikely.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with snake_case: add_mcp_server, exec_mcp_tool, and search_mcp_server. This predictable naming scheme enhances readability and usability for agents.
Tool Count3/5With only 3 tools, the server feels thin for a router's scope, which typically involves more operations like listing, updating, or removing servers. While the core functions are present, the count is borderline for comprehensive routing capabilities.
Completeness3/5The tool set covers basic registration, execution, and search, but lacks operations for updating or deleting servers, which are common in lifecycle management. This creates notable gaps that agents might need to work around for full server management.
Average 2.9/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
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 states the tool executes another tool but does not describe execution behavior such as error handling, permissions required, side effects, or response format. This is a significant gap for a tool that performs dynamic execution, as it lacks details on safety, reliability, or operational constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with a clear purpose statement followed by a parameter list. Every sentence serves a purpose, and there is no redundant or verbose content. However, the structure could be improved by integrating parameter details more seamlessly rather than a separate 'Args:' section, slightly reducing readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (dynamic execution with 3 parameters, nested objects, and an output schema), the description is incomplete. It lacks behavioral context, usage guidelines, and parameter details. The presence of an output schema mitigates the need to explain return values, but the description does not adequately cover execution semantics or integration with sibling tools, leaving gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters with brief explanations (e.g., 'Name of the target server'), but these add minimal semantic value beyond the schema's property names. The description does not explain parameter formats, constraints, or how 'parameters' should be structured, leaving key details undocumented for a tool with 3 required parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Execute a tool on a target MCP server,' specifying the verb 'execute' and resource 'tool on a target MCP server.' It distinguishes from sibling tools like 'add_mcp_server' and 'search_mcp_server' by focusing on execution rather than server management or searching. However, it lacks specificity about what types of tools can be executed or the execution context, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It does not mention prerequisites (e.g., needing an added server via 'add_mcp_server'), exclusions, or contextual cues for selection. Usage is implied only through the tool name and description, with no explicit instructions for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Register') but doesn't cover critical aspects like authentication requirements, potential side effects (e.g., if registration is idempotent or destructive), rate limits, or error handling. This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with a clear purpose statement followed by a bulleted list of parameters. Each sentence earns its place, though the parameter explanations could be slightly more detailed without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation with 4 parameters), no annotations, and an output schema present (which reduces the need to describe return values), the description is moderately complete. It covers the basic action and parameters but lacks behavioral context and usage guidelines, making it adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It lists all four parameters with brief explanations (e.g., 'Unique name of the server'), adding basic meaning beyond the schema's titles. However, it doesn't provide details on formats (e.g., URL validation for server_endpoint) or constraints (e.g., uniqueness rules for server_name), leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Register') and resource ('new MCP server with the discovery service'), making the purpose evident. However, it doesn't explicitly differentiate this tool from its siblings (exec_mcp_tool and search_mcp_server), which would require mentioning that this is for registration rather than execution or search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like exec_mcp_tool or search_mcp_server. The description lacks context about prerequisites (e.g., whether the server must be pre-configured) or exclusions, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks behavioral details. It doesn't disclose whether this is a read-only operation, what the search scope is (e.g., local vs. remote), performance characteristics, or error handling. The mention of 'registered MCP servers' hints at a database query, but specifics are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by a structured 'Args:' section. It avoids unnecessary words, but the 'Args:' formatting could be more integrated. Overall, it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with 0% schema coverage and an output schema present, the description provides basic parameter semantics but lacks behavioral context. It doesn't explain search mechanics or result format, relying on the output schema for return values. This is adequate for a simple search tool but misses operational details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds basic semantics by explaining 'query' as a 'Search query' and 'top_k' as 'Number of top results to return', which clarifies intent beyond schema types. However, it doesn't detail query syntax, result ranking, or default behavior beyond the default value, leaving gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Search') and resource ('registered MCP servers'), making the purpose immediately understandable. It distinguishes from sibling tools like 'add_mcp_server' (creation) and 'exec_mcp_tool' (execution) by focusing on discovery. However, it doesn't specify what aspects of servers are searched (e.g., names, descriptions, capabilities), keeping it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, typical use cases, or how it relates to sibling tools like 'add_mcp_server' for adding servers or 'exec_mcp_tool' for using them. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Maverick-LjXuan/mcp-router'
If you have feedback or need assistance with the MCP directory API, please join our Discord server