RouterBase MCP
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool serves a distinct purpose: chat completion, model metadata, pricing, integration guide, and model listing. No overlap or ambiguity.
Naming Consistency5/5All tools follow a consistent 'routerbase_verb_noun' pattern, e.g., routerbase_list_models, routerbase_chat_completion. Predictable and uniform.
Tool Count5/5With 5 tools, the server is well-scoped for its purpose as an API wrapper. It covers essential operations without being overly minimal or bloated.
Completeness5/5The tool set covers the full lifecycle for interacting with RouterBase: listing models, getting details, pricing, making API calls, and onboarding. No obvious gaps.
Average 3.1/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 8 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
This repository is licensed under MIT License.
This repository includes a README.md file.
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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, and the description does not disclose behavioral traits such as side effects, permissions, or data source. It only states it returns a guide, which is insufficient for full transparency.
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 single and concise, with no wasted words. However, it could be slightly more detailed without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should clarify the return format or content. The mention of a 'canonical routerbase backlink' is vague, and the guide's structure or depth is not explained.
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?
The input schema already fully describes the 'language' parameter with enum and default. The description adds no additional meaning or context about this parameter, failing to compensate for the already high schema coverage.
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 returns a RouterBase integration guide, which distinguishes it from siblings like chat completion or model listing. It is specific with verb 'Return' and resource 'integration guide'.
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 on when to use this tool versus its siblings. The description does not mention use cases or prerequisites, leaving the agent to infer from the tool name.
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?
No annotations provided, so description must cover behavioral traits. It only states it calls the API, omitting details like side effects (mutation), rate limits, authentication specifics, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence is too brief for a tool with 5 params and no annotations. It lacks important details, making it underspecified rather than effectively concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and multiple parameters, the description fails to explain return values, behavior, or usage context, leaving significant gaps.
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 covers 60% of parameters with descriptions. Tool description adds no value beyond schema; undocumented parameters (max_tokens, temperature) lack any semantic help in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calls the OpenAI-compatible chat completions API via RouterBase, using specific verb and resource. It distinguishes from sibling tools which are about model info, pricing, etc.
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 explicit guidance on when to use this tool vs alternatives. Usage is implied by the purpose, but the description lacks context about required setup or when NOT to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only says 'Fetch metadata' with no behavioral details such as whether it is read-only, any required permissions, rate limits, or side effects. With no annotations provided, the description carries the full burden and fails to disclose basic traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is front-loaded and gets straight to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 parameters, no output schema, and no annotations, the description is insufficient. It does not explain what metadata is returned, any usage constraints, or the relationship to other tools. For a simple fetch it is barely adequate.
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 coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond what the schema already provides; it simply restates the purpose without detailing parameter formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch metadata') and the resource ('a specific RouterBase model id'). This is a specific verb+resource pair that distinguishes it from sibling tools like routerbase_chat_completion (different verb) and routerbase_list_models (different resource).
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 the siblings. For example, it does not explain when to fetch details for a single model versus listing all models with routerbase_list_models. No preconditions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that the operation is fetching (read-only), but does not mention authentication requirements, rate limits, or behavior when api_key is missing. Minimal disclosure beyond the action itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
One concise sentence with no fluff. Front-loaded with verb and resource, perfectly sized for a simple pricing tool.
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?
Simple tool with no output schema. Description covers what it does but omits return format or pagination. Given simplicity, it's adequate but could benefit from stating the output structure.
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 coverage is 100% with clear parameter descriptions. The description adds marginal value ('Omit to list all pricing' is already in schema). Baseline 3 is appropriate since schema already explains parameters well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch', resource 'RouterBase pricing', and specifies the scope: one model or all active models. It distinguishes from sibling tools like routerbase_chat_completion and routerbase_list_models by focusing on pricing data.
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 explicit guidance on when to use this tool vs alternatives. The description implies usage by omitting model_id for all pricing, but lacks context like prerequisites or comparisons to sibling tools.
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?
No annotations are provided, and the description is minimal. It does not disclose behavioral traits such as pagination behavior, authentication needs (though api_key param exists), rate limits, or what the output contains. The description adds little beyond the obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It captures the core action and variability efficiently.
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?
The description is adequate for a simple list tool, but given 6 parameters, no output schema, and no annotations, it could provide more context about output format, pagination details, or defaults. It is minimally complete.
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 100%, so parameters are well-documented in the schema. The description adds no new semantic meaning beyond reiterating that filters exist. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'List RouterBase models' and specifies optional filters (modality, provider, search), distinguishing it from siblings like routerbase_get_model (single model) and routerbase_chat_completion (chat).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for listing with optional filters but does not explicitly state when to use it over alternatives or provide any when-not-to-use guidance. Sibling tools exist, but no differentiation criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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