MCP Credentials Broker

by ars-system

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Server Quality Checklist

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Latest release: v1.0.4
Disambiguation5/5
Each tool targets a distinct operation: storage, reference issuance, reference resolution, token minting, token revocation, OAuth initiation, and stats. The two-step get_secret/resolve_secret flow is clearly distinguished by their descriptions, and mint_token vs start_oauth_flow differentiate direct minting from interactive OAuth.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., get_secret, mint_token, revoke_token, start_oauth_flow, get_broker_stats). No mixed conventions.
Tool Count5/5
7 tools is well-scoped for a credentials broker, covering core operations without redundancy or bloat.
Completeness4/5
The surface covers the full lifecycle of storing, referencing, resolving, minting, and revoking credentials, plus OAuth and stats. Minor gaps include lack of explicit delete/update for secrets or a listing API, but the core workflows are complete.
Average 3.9/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
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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?
With no annotations provided, the description carries the full burden for behavioral disclosure. It only states the basic store action and a reference workflow, but does not reveal key behaviors such as whether existing secrets are overwritten, any permission requirements, or what the response/return value looks like. This is a significant gap 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and immediately communicates the core action and a key follow-up usage. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple store operation, the description explains the purpose and how the stored secret is consumed. However, without annotations or an output schema, it lacks information on edge cases (e.g., overwriting, errors) and security context, making it adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter (name, value, tags) already having a description. The tool description adds no extra parameter-level detail, so the baseline of 3 applies because the schema carries the explanatory weight.
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 verb 'Store' and the resource 'a secret in the credentials broker', making the tool's purpose unambiguous. It also distinguishes from siblings by noting the secret can later be referenced with get_secret, which positions store_secret as the write counterpart.
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 provides clear context by indicating the workflow: store a secret, then reference it via get_secret. However, it does not explicitly state when NOT to use this tool or discuss alternatives like mint_token or revoke_token, so it stops short of full guidance.
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?
With no annotations, the description carries the burden of behavioral disclosure. It implies a read-only operation ('Get statistics') and lists what data is returned, but does not explicitly state side effects, permission requirements, or whether it is safe. The context is useful but leaves some ambiguity.
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?
The description is a single, front-loaded sentence that conveys the tool's purpose without unnecessary words. It is concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and no output schema, the description provides a reasonable overview of the return content. It mentions three key categories, which is adequate, though it could be more explicit about the response format or exact metrics.
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?
The tool has 0 parameters, so the baseline is 4. The description does not need to add parameter details, and the schema is fully covered vacuously.
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's function: 'Get statistics about the credentials broker' with specific items (active tokens, secret references, audit log summary). This is a specific verb+resource and distinguishes it from sibling tools that focus on individual secret/token operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 vs alternatives. It simply describes what it does, without any explicit context, prerequisites, or exclusions.
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?
Without annotations, the description carries the burden. It discloses the immediate effect and that the token becomes invalid, but does not mention whether revocation is irreversible, idempotent, or requires specific permissions. Some behavioral information is provided but gaps remain.
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?
The description is a single, front-loaded sentence with no wasted words. It efficiently conveys the action and consequence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description covers the core purpose and effect. It lacks explicit usage guidelines and edge-case behavior, but is largely sufficient for an agent to understand the tool's role. Slightly above adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter token_id is fully documented in the schema with 100% coverage, so the description adds no additional semantic meaning beyond what the schema provides. Baseline 3 applies.
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's function: revoking a previously issued token. The verb 'revokes' is specific and the resource 'token' is explicit, distinguishing it from sibling tools like 'mint_token'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used after a token has been issued ('previously issued token'), but does not explicitly state when to use it over alternatives or mention any prerequisites or exclusions. Usage context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and discloses meaningful lifecycle behavior: the token is short-lived and automatically revoked after the TTL expires. This goes beyond the schema, though it does not mention permissions or failure modes.
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?
The description is two sentences, front-loaded with the core action, and contains no filler. Every phrase contributes meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description should cover return value/behavior, but it only defines the token's lifecycle. It omits what the tool returns (e.g., the token string) and error conditions, making it adequate but not fully complete for a 4-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter is already documented. The description adds context around 'scoped' and 'TTL expires,' which loosely connects to scopes and ttl_seconds, but it does not provide deeper syntax or formatting details beyond the 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?
The description uses a specific verb ('Generates') plus a concrete resource ('short-lived, scoped token') and enumerates target providers. This clearly distinguishes it from sibling tools like revoke_token or get_secret.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when a short-lived, scoped token for a specific provider is needed. However, it does not explicitly contrast with alternatives like start_oauth_flow or revoke_token, leaving usage guidance mostly implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It discloses a critical behavior—returning a reference ID instead of the raw secret—and mentions expiry/TTL, which is essential given the tool name. It does not cover permissions, error handling, or side effects, but the key behavior is transparent.
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?
The description is two concise sentences, front-loaded with the primary behavior and return value. Every sentence adds value, with no redundant or extraneous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description must explain return values; it does so by stating a reference ID and expiry time. It covers the essential behavior and TTL mechanism, though it does not detail return structure or error cases. The required parameters are documented in the schema, so the description is adequately complete for invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description mentions TTL period, aligning with the schema, but adds no additional semantic detail beyond what the property descriptions already provide.
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 uses a specific verb ('issues') and resource ('short-lived secret reference'), clearly stating the tool's function. It distinguishes itself from siblings by explicitly noting it returns a reference ID rather than the raw secret, which differentiates it from tools like resolve_secret.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by explaining that the reference can be used to retrieve the actual secret within the TTL, suggesting a companion tool. However, it does not explicitly name alternatives or state when not to use this tool, leaving the agent to infer the appropriate scenario.
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 are provided, so the description carries the burden. It states the action (resolve) and the result (actual token value), which implies a read operation. However, it does not disclose that the token is sensitive or that handling it has security implications—context an agent might need for safe invocation.
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 sentences, first states the core action and source, second gives a concrete usage scenario. No redundant information; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is nearly complete: purpose, source, and usage are covered. It could mention that the returned token is sensitive and should be handled cautiously, but that is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes the single parameter (reference_id) as returned by get_secret, so baseline 3 applies. The description adds no additional semantic detail beyond what the schema provides.
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's purpose: resolving a secret reference ID to the actual token value. It specifies the source (from get_secret) and distinguishes it from sibling tools like store_secret or mint_token.
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?
It explains when to use the tool: when you need the real token to pass to another MCP tool. It does not explicitly rule out alternatives, but the context is clear enough for an agent to know this is the intended resolution step.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the transparency burden. It discloses that the tool opens a browser, requires no client credentials from the user, and stores the access token under a secret_name. It lacks details about output/return behavior and overwrite semantics, but covers core side effects.
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 sentences, front-loaded with the action, no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description adequately explains the tool's purpose and side effects, but doesn't mention what the tool returns or failure behavior. It's a reasonable but not exhaustive description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all five parameters. The description adds minimal extra parameter context, such as how secret_name is used with get_secret/resolve_secret, but the schema already documents parameters thoroughly. Baseline 3 is appropriate.
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 authenticates a provider via browser-based OAuth2 web flow, distinguishing it from sibling secret management tools like get_secret and store_secret. It also explains the token storage for later retrieval.
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?
It implies usage by noting no client_id or client_secret is needed and that the token is stored for use with get_secret/resolve_secret. However, it doesn't explicitly compare to alternatives or state exclusions, so it's not as strong as the calibration best case.
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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