idm-mcp

by fcapub

Overview Schema Related Servers Score Discussions

Python

Hybrid

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: echo/ping for testing, get_did/resolve_did for DIDs, get_vc/list_credentials/resolve_vc/verify_vc for VCs. Overlap between list_credentials and resolve_vc is resolved by parameter differences.
Naming Consistency5/5
Tool names follow a consistent verb_noun pattern (get_did, get_vc, list_credentials, resolve_did, resolve_vc, verify_vc) with lowercase snake_case. echo and ping are conventional single-word utilities.
Tool Count5/5
Eight tools cover both DID and Verifiable Credential management appropriately without being excessive or insufficient for a focused identity server.
Completeness4/5
Core workflows (create/resolve DID, issue/list/resolve/verify VC) are covered. Minor gaps like DID update/deactivation or issuer management are absent but acceptable for a basic identity server.
Average 4.3/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 15 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
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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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses validation (pk must decode to 32 bytes), return value (DID record dict with 'id'), and storage behavior (values stored in document). However, it does not mention whether the operation is idempotent or what happens on duplicate keys.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized with bold headings for required and optional sections, making it scannable. It is somewhat verbose but each sentence adds value. Slight reduction could improve conciseness.
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 output schema, the description adequately covers what is returned (DID record dict with 'id'). It also explains validation and metadata recording. Missing are error states (e.g., duplicate key) and permission requirements, but overall it is fairly complete for a creation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description fully compensates. It adds crucial meaning for each parameter: pk format and validation, pktype algorithm label, and metadata fields' purpose. This goes well beyond the schema's empty titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create a DID record', which is a specific verb+resource, but the tool name 'get_did' is misleading as it implies retrieval rather than creation. This could confuse the agent, especially given sibling 'resolve_did' which actually retrieves. The description does not explicitly differentiate from siblings.
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 lists required and optional fields with clear sections, implying usage context. However, it does not explicitly state when to use this tool versus alternatives like 'resolve_did', nor does it specify prerequisites or conditions for use.
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 covers signing by issuer key, canonical serialization, and the reserved signType, providing good behavioral details beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with a clear parameter list followed by behavioral notes. Every sentence adds value, though slightly long for a concise tool definition.
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?
Despite no output schema, the description mentions return value. It covers input and signing behavior but lacks details on storage location, errors, or permission requirements, which is acceptable given tool complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description compensates fully by explaining each parameter with concrete examples (e.g., 'callTools', 'Ed25519') and clarifying purpose, adding significant value.
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 it issues a Verifiable Credential for a subject DID and stores it, with relation to get_did. This distinguishes it from siblings like resolve_vc or verify_vc.
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?
It implies usage for authorization and references get_did for subjectID, but does not explicitly state when to use or avoid, nor compare to alternatives like list_credentials.
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?
The description implies a safe, side-effect-free operation. With no annotations, it sufficiently covers expected behavior for a simple echo.
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 concise sentences with front-loaded purpose and no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
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 output schema, the description is complete enough to guide use.
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?
Parameter 'message' is clarified as the input to echo, but schema description coverage is 0%, and the description adds no further constraints or format details.
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?
Clearly states the tool echoes back a message. Distinct from siblings which handle DIDs, VCs, and ping.
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?
Explicitly states usefulness for testing argument passing, providing clear context for when to use it. No exclusion or alternative needed due to simplicity.
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?
The description clearly states the tool returns a fixed response ('pong') for health checking. Since there are no annotations, the description adequately covers the expected behavior for a simple, side-effect-free 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 extremely concise with two sentences, containing no unnecessary words. It is front-loaded with the key action ('Health check') and delivers value efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, simple return value), the description is complete. It explains the input, behavior, and output. The presence of an output schema further reduces the need for description detail.
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 input schema has no parameters, so the description does not need to add parameter details. Baseline is 4 for zero parameters, and the description is sufficient.
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 explicitly states it is a health check that returns 'pong', clearly indicating the tool's purpose and resource. It is easily distinguishable from sibling tools which relate to DIDs and credentials.
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 for connectivity verification but does not provide explicit guidance on when to use it versus alternatives like 'echo' or when not to use it. No exclusions are mentioned.
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?
No annotations are provided, so the description carries the full burden. It discloses that it returns a dict or list depending on input, and raises ValueError for unknown vc_id. No side effects are mentioned, but for a read-like operation this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear front-loaded first sentence. The parameter explanation is integrated without being overly verbose. It 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 optional parameter, the description covers the dual behavior, error condition, and return types. It is complete enough for the agent to use correctly.
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 schema has 0% description coverage, so the description adds significant value. It explains the vc_id parameter's meaning, its default behavior, and the return type for each case, which is 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 dual functionality: resolve a VC by ID or list all issued credentials. The verb 'Resolve' is specific and the resource is 'Verifiable Credential'. It distinguishes itself from siblings like 'get_vc' by explicitly mentioning both modes.
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 explains when to use each mode based on the vc_id parameter: if omitted/empty, list all; if provided, resolve that specific VC. It does not compare with sibling tools, but the condition is clearly stated.
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 clarifies the return: a list of VCs matching the subject DID, or empty if none. This discloses the behavioral outcome. It does not mention side effects or auth needs, but since this is a read-only list, the description is sufficiently 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 concise: two sentences for purpose and parameter, plus a note on return. No unnecessary words, and the main action is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single parameter, list output), the description covers what it does, parameter explanation, and return value. It is complete for an agent to use correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description adds critical meaning: subject is the 'subject DID (credentialSubject.id)'. This clarifies the parameter semantic beyond the schema's bare type definition.
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 'List all Verifiable Credentials issued to a subject DID', specifying the action (list), resource (VCs), and scope (by subject). It distinguishes from sibling tools like get_vc or resolve_vc by focusing on listing multiple credentials for a given subject.
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 for listing VCs of a specific subject but does not explicitly mention when to use vs. alternatives (e.g., get_vc for a single VC). No exclusions or alternative conditions are provided.
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?
The description discloses key behavioral traits: it returns a dict for a specific DID, a list of documents when no DID is given, and raises ValueError for unknown DIDs. Since no annotations are provided, the description carries the full burden and does so effectively.
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 concise, with a clear front-loaded sentence followed by a brief parameter explanation and return values. Every sentence adds value without unnecessary wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with an output schema (implied), the description adequately covers return types, error behavior, and parameter semantics. It is complete for the level of complexity.
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 description adds significant meaning beyond the schema: it explains the did parameter's role, gives an example format, and describes the special behavior when omitted. With 0% schema coverage, this compensation is strong.
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: resolve a DID to its document or list all DIDs. It specifies the verb 'resolve' and the resource 'DID document', and distinguishes between the two behaviors based on the parameter. This differentiates it from siblings like get_did.
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 on when to use the tool (to resolve a specific DID or list all DIDs). It does not explicitly state when not to use it or mention alternatives, but the dual behavior is well explained.
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. It details the verification process: resolving public key from DID document, rebuilding signed bytes, checking Ed25519 signature, and checking validity window. It also notes it works for any issuer registered via get_did. However, it does not describe error conditions or edge cases.
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 well-structured and front-loaded with the main purpose, followed by detailed process and constraints. Each sentence adds value without redundancy. It is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides the return object shape {valid, issuer, subjectId, reason}. It explains the verification steps and clarifies scope (authenticity vs. trust). This gives an AI agent complete context to invoke the tool correctly.
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 input schema only defines 'vc' as an object with no constraints (0% schema coverage). The description adds significant meaning by explaining which parts of the VC are used (proof.proofValue, validFrom, validUntil) and that the proof is reset to empty string for verification. This compensates for the sparse 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 clearly states it verifies the issuer signature and validity window of a Verifiable Credential, specifying the verb (verify) and resource (VC). It distinguishes from sibling tools like get_did and resolve_did by focusing on credential validation rather than DID resolution.
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 explains when to use the tool (to confirm authenticity of a VC's signature and validity window) and explicitly states what it does NOT do (assess issuer trust/authorization), providing clear context. However, it does not explicitly mention alternative tools for trust assessment.
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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