mcp-oidc4vci
MCP-OIDC4VCI
Emisión de Credenciales Verificables asistida por IA mediante MCP
Este proyecto explora cómo se puede utilizar el Model Context Protocol (MCP) para exponer capacidades de un ecosistema de OpenID for Verifiable Credential Issuance (OIDC4VCI) a un agente de IA. Se dirige a OIDC4VCI 1.0 (especificación final).
El objetivo no es sustituir a una cartera ni dar a un LLM acceso a claves privadas o a credenciales sin restriciones. En su lugar, el proyecto investiga una arquitectura más restringida:
Un servidor MCP actúa como capa de orquestación orientada al agente para comprender y avanzar en un flujo de emisión de credenciales OIDC4VCI, mientras que las operaciones sensibles para la seguridad permanecen bajo el control de componentes dedicados, como la cartera o el titular de la credencial.
El proyecto parte de un escenario concreto:
Un usuario recibe una oferta de credencial OIDC4VCI y quiere que un agente de IA le ayude a comprender qué se le está ofreciendo y a guiar u orquestar el proceso de emisión.
Motivación
OIDC4VCI define un protocolo para emitir Credenciales Verificables a una cartera o al titular de una credencial. Un flujo típico implica una oferta de credencial, un emisor de credenciales y sus metadatos, un servidor de autorización, flujos de autorización o preautorizados, solicitudes de credencial, pruebas y vinculación de claves criptográficas, y la entrega y el almacenamiento de la credencial: una cantidad significativa de información estructurada que el usuario debe interpretar por sí mismo.
Un agente de IA puede ayudar potencialmente al comprender una oferta de credencial, explicar qué se está ofreciendo, descubrir las configuraciones de credenciales admitidas, determirar el flujo de emisión requerido, identifivar qué se necesita a continuación y orquestar interacciones de protocolo no sensibles.
La pregunta central que explora este proyecto es:
¿Cómo se pueden exponer las capacidades de OIDC4VCI a un agente de IA a través de MCP sin comprometer las fronteras de seguridad de las carteras y del material de claves criptográficas?
Para el diseño completo del sistema, ver Arquitectura. Para el desarrollo previsto y el alcance actual, ver Hoja de ruta.
Related MCP server: Cheqd MCP Toolkit
Arquitecura de un vistazo
AI Agent ──MCP──▶ OIDC4VCI MCP Server ──▶ Credential Issuer / Authorization Server
│
▼
Wallet Boundary
│
▼
Key Management / Proofs / User AuthorizationEl servidor MCP actúa como intermediario entre el agente de IA y el ecosistema OIDC4VCI — no debe convertirse automáticamente en una cartera. Las operaciones sensibles (claves, pruebas, consentimiento) permanecen tras una frontera explícita de cartera, nunca en el contexto del LLM.
Los detalles completos, las responsabilidades de los componentes, los flujos de datos, los contratos de las herramientas y los requisitos de seguridad se encuentran en docs/ARCHITECTURE.md.
Estado del proyecto
Fase inicial. La arquitecura y el alcance del MVP están esbozados en docs/ARCHITECTURE.md y docs/ROADMAP.md.
Fase 1 (Inspector de ofertas de credencial MCP) — completada. inspect_credential_offer resuelve una oferta de credencial por valor o por referencia (credential_offer_uri), la valida contra OIDC4VCI 1.0 y devuelve el emisor, los IDs de configuración de credenciales solicitados y los grants. Ver src/mcp_oidc4vci/credential_offer.py.
Fase 2 (Descubrimiento de metadatos) — completada. get_credential_issuer_metadata obtiene y valida los metadatos de un emisor de credenciales desde su endpoint well-known (insertando correctamente el segmento de ruta well-known antes de cualquier componente de ruta en el identificador del emisor, según la especificación), verifica que el credential_issuer devuelto coincide con lo solicitado y devuelve el endpoint de credenciales, los servidores de autorización y las configuraciones de credenciales admitidas. Ver src/mcp_oidc4vci/credential_issuer_metadata.py.
Fase 3 (Motor de flujo de emisión) — completada. describe_issuance_flow, initiate_issuance y get_issuance_status están implementados sobre un IssuanceSessionStore en memoria. Para el grant de código preautorizado, initiate_issuance completa la solicitud de token real (descubrimiento del servidor de autorización OAuth mediante RFC 8414 y, a continuación, el intercambio de token); para el grant de código de autorización se detiene en waiting_for_user_authorization, ya que completar ese flujo requiere la redirección impulsada por la cartera que la Fase 4 tampoco cubre (ver más abajo). Ver src/mcp_oidc4vci/issuance.py, src/mcp_oidc4vci/authorization_server_metadata.py y src/mcp_oidc4vci/token_request.py.
Fase 4 (Frontera de cartera) — completada (alcance reducido). WalletAdapter (un Protocol con generate_proof y receive_credential) y MockWalletAdapter respaldan la nueva herramienta request_credential, que completa la Solicitud de Credencial para una sesión ready_for_credential_request: obtener metadatos del emisor, conseguir un nonce nuevo si el emisor lo necesita, pedir a la cartera una prueba firmada (una prueba real openid4vci-proo+jwt firmada con EC, nunca firmada por este servidor), enviarla mediante POST y entregar la credencial emitida a la cartera — su contenido nunca llega al agente. El grant de código preautorizado ahora funciona de extremo a extremo. Ver src/mcp_oidc4vci/wallet.py, src/mcp_oidc4vci/credential_request.py y src/mcp_oidc4vci/nonce.py.
Los modelos de datos compartidos se encuentran en src/mcp_oidc4vci/models.py, con las pruebas en tests/ (99% de cobertura, 124 pruebas).
Stack Tecnológico
Python — lenguaje de implementación.
uv — gestión de dependencias, entornos virtuales y ejecución del proyecto.
FastMCP — framework Python de alto nivel para construir el servidor MCP y sus herramientas.
MCP Python SDK — el SDK oficial de protocolo subyacente sobre el que se basa FastMCP.
MCP Inspector — herramienta interactiva para probar y depurar las herramientas del servidor MCP durante el desarrollo.
Primeros pasos
# Install uv if you don't have it
curl -LsSf https://astral.sh/uv/install.sh | sh
# Install dependencies
uv sync
# Run the MCP server through the MCP Inspector for interactive testing
uv run fastmcp dev inspector src/mcp_oidc4vci/server.py:mcp
# Lint, type-check, and run the test suite
uv run ruff check .
uv run mypy src
uv run pytestDocumentación
Arquitectura — componentes, principios de diseño, frontera de cartera, flujo de datos, contratos de herramientas MCP, requisitos de seguridad.
Hoja de ruta — alcance del MVP, fases de desarrollo, no objetivos, criterios de éxito, extensiones futuras.
Available Tools
6 toolsdescribe_issuance_flowB
Describe the steps required to obtain the credential(s) offered by a Credential Offer.
Resolves the offer and returns which grant-based flow applies and its ordered steps.
| Name | Required | Description | Default |
|---|---|---|---|
| credential_offer | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for disclosing behavior. It states that the tool 'resolves' the offer and returns the applicable flow, which implies a read/analysis operation rather than a mutating one. It does not address side effects, permissions, or edge cases, but the 'Describe' framing makes the operation's non-destructive nature reasonably clear.
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 definition is two short sentences with no waste; the first sentence states the purpose and the second adds detail about the output (grant-based flow and ordered steps). It is concise and front-loaded, though the first sentence is slightly redundant with the tool name.
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?
For a single-parameter tool with an output schema, the description covers the core purpose and result well. However, it lacks explicit usage boundaries, mentions no sibling alternatives, and does not clarify the credential_offer input format. Without annotations, these gaps leave the agent with some uncertainty about when and how to invoke it correctly.
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 schema has 0% description coverage for the only parameter, so the descrition must compensate. It mentions that the input relates to a 'Credential Offer', but it does not explain the expected string format, encoding, source, or any constraints on credential_offer. This is insufficient for an agent to confidently construct the parameter value.
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 uses a specific verb 'Describe' and names the resource: the issuance flow for a Credential Offer. It further clarifies the output by saying it returns which grant-based flow applies and its ordered steps. However, it does not explicitly differentiate this from sibling tools like inspect_credential_offer or initiate_issuance, so it stops short of a 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 implies usage when the agent needs the ordered steps to obtain credentials from an offer, but it does not explicitly state when to use this tool instead of siblings such as inspect_credential_offer, initiate_issuance, or request_credential. It offers no exclusions, prerequisites, or alternative-routing guidance, so the usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_credential_issuer_metadataA
Fetch and validate a Credential Issuer's metadata from its well-known endpoint.
Returns the issuer's credential endpoint, authorization servers, and the credential configurations it supports.
| Name | Required | Description | Default |
|---|---|---|---|
| credential_issuer | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses that the tool fetches over a well-known endpoint and performs validation, and it states the returned data. However, it does not clarify what 'validate' means in practice, what happens on invalid metadata, or whether any external network/auth considerations exist.
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?
Two tight sentences with no filler. The main action is front-loaded, and the return-value sentence adds necessary detail without repetition.
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?
The tool is simple with one parameter and an output schema, and the description covers the core action and returned fields. It is incomplete regarding parameter format and validation failure behavior, but for a basic metadata fetch it is close to adequate.
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?
Schema coverage is 0%, so the description must compensate for the undocumented 'credential_issuer' parameter. The description implies the parameter identifies the issuer whose metadata is fetched, but it never explicitly explains the expected format (e.g., URL, identifier). This is enough for a single obvious parameter but not fully explicit.
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 uses a specific verb ('Fetch and validate') and names the resource ('Credential Issuer's metadata') plus the well-known endpoint location. It also lists the concrete return contents (credential endpoint, authorization servers, credential configurations), which clearly distinguishes this tool from siblings like get_issuance_status or inspect_credential_offer.
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 implies when to use it (when you need issuer metadata), but it gives no explicit guidance, no contexts to avoid, and does not mention any sibling alternative. An agent must infer usage from the tool name and general purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_issuance_statusB
Return the current state of a previously started issuance session.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
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. 'Return the current state' signals a read-only status check, which is the main behavioral trait, but it does not explain what happens for invalid or expired session IDs, or whether the state is refreshed or cached.
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 concise sentence that is front-loaded with the action and resource. Every word contributes meaning, and there is no redundant or filler content.
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?
For a simple one-parameter status lookup, the description is minimally adequate, especially since an output schema exists. However, it lacks explicit guidance on where session_id comes from, when to call the tool, and how errors are surfaced.
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?
Schema description coverage is 0%, and the description only indirectly references the session parameter by saying 'previously started issuance session.' It does not explicitly state that session_id is the identifier returned from initiate_issuance, nor describe its format or expected provenance.
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 uses a specific verb ('Return') and resource ('current state of a previously started issuance session'), making the tool's core purpose unambiguous. It is distinct from siblings like initiate_issuance and request_credential, though it does not explicitly name those alternatives.
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 phrase 'previously started' implies the tool should only be used after an issuance session has been initiated, which gives some contextual guidance. However, it does not explicitly state when to use this tool versus alternatives or mention related tools like inspect_credential_offer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
initiate_issuanceA
Start an issuance session for a Credential Offer.
For the pre-authorized code grant, completes the token exchange immediately and the
session ends ready_for_credential_request or failed. For the authorization code
grant, the session is left waiting_for_user_authorization, since completing it requires
a wallet-driven redirect not yet implemented. tx_code is the transaction code obtained
from the user out-of-band, if the offer requires one.
| Name | Required | Description | Default |
|---|---|---|---|
| tx_code | No | ||
| credential_offer | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden and does so thoroughly. It discloses immediate token exchange for pre-authorized grants, terminal states ready_for_credential_request or failed, the waiting_for_user_authorization state for the authorization code grant, the unimplemented redirect, and the out-of-band nature of tx_code.
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 three focused sentences, front-loaded with the action and then expanding only into necessary flow-specific behavior. Every sentence adds operational value, with no filler or repetition of schema types.
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?
For a complex issuance flow, the description covers the two grant types, their outcomes, the current implementation limitation, and the tx_code input. Since an output schema exists, return-value details are already handled outside the description, and nothing essential to invoking the tool correctly is missing.
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 no descriptions, so the description must compensate. It explains tx_code well ('transaction code obtained from the user out-of-band, if the offer requires one'), but credential_offer remains only implicitly defined as the offer that starts the session, with no format or origin details.
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 opens with a specific verb and resource: 'Start an issuance session for a Credential Offer.' It further clarifies the operation by describing distinct grant-type behaviors and resulting session states, making it unmistakable from siblings like get_issuance_status or request_credential.
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 implies usage by saying 'Start an issuance session' and details what happens for each grant type, but it never explicitly contrasts with sibling tools or states when not to use it. The guidance is mostly behavioral rather than decision-oriented, leaving alternatives unmentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
inspect_credential_offerA
Parse and validate an OIDC4VCI Credential Offer URI.
Resolves the offer (by value or by reference) and returns its Credential Issuer, requested credential configuration IDs, and available grants.
| Name | Required | Description | Default |
|---|---|---|---|
| credential_offer | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral burden. It does disclose useful behavior: it resolves the offer 'by value or by reference' and returns specific data. But it says nothing about validation failure modes, networking behavior, or side effects, which matters for a resolve/validate operation.
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?
Two sentences with no filler. The main action is front-loaded, and the second sentence adds the behavioral and output details an agent needs. Every sentence earns its place.
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?
The tool has only one parameter and an output schema, so the return shape is already covered. The description adds the key resolution distinction and output highlights. Minor gaps are validation behavior and explicit exclusions, but overall an agent can invoke this correctly with the information provided.
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?
Schema coverage is 0% and the schema only says credential_offer is a string. The description compensates by explaining it is a Credential Offer URI and that it can be resolved by value or by reference, giving the agent meaningful semantic context for the sole parameter beyond the raw type.
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 opens with a specific verb and resource ('Parse and validate an OIDC4VCI Credential Offer URI') and then lists the concrete outputs (Credential Issuer, configuration IDs, grants). This makes it clearly distinct from the sibling issuance-and-status tools, which focus on different stages of the protocol.
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 intended trigger is inferrable: an agent should use this when it has an OIDC4VCI Credential Offer URI to inspect. However, the description never explicitly says when to prefer this over siblings or when not to use it, so the usage guidance is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
request_credentialA
Complete the Credential Request for a session that has an access token.
Generates a key proof of possession through the wallet adapter — this server never signs anything itself — and hands the issued credential to the wallet for safekeeping. Its contents are never returned to the agent.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full transparency burden. It discloses the proof-of-possession generation through the wallet adapter, the server's deliberate non-signing role, and the critical constraint that the issued credential's contents are never returned to the agent. These are non-obvious behaviors an agent needs to know.
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 two sentences: the first names the action and precondition, the second adds the key behavioral details. Every clause carries information; no filler or repetition. It is well front-loaded for an agent scanning the tool list.
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?
For a one-parameter tool with an output schema, the description covers the main action, important side effects, and the session precondition. It does not explicitly place itself in the issuance flow relative to siblings, but the access-token condition and 'completes' wording give enough context for correct invocation.
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?
With 0% schema description coverage, the description must supply parameter meaning. It adds that session_id refers to a session that already has an access token, which is useful, but it does not say where that session_id comes from (e.g., initiate_issuance) or provide format/source details. This is minimal compensation for a schema with a bare string parameter.
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 opens with a specific verb and resource: 'Complete the Credential Request for a session that has an access token.' It also clarifies the outcome (credential handed to wallet) and highlights a distinguishing behavior (server never signs; contents never returned), which sets it apart from sibling inspection and initiation tools.
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 states a clear precondition — the session must already have an access token — which implicitly tells the agent when in the flow to call it. It does not explicitly compare it against siblings like get_issuance_status or inspect_credential_offer, so it misses the full 'when not to use' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Each tool targets a distinct phase of the OIDC4VCI flow, but inspect_credential_offer and describe_issuance_flow both resolve an offer and could be confused by an agent deciding whether to inspect contents or get next steps. The remaining tools have clearly separate boundaries.
All six tools use a consistent snake_case verb_noun pattern, e.g. get_, inspect_, describe_, initiate_, and request_. There is no casing or verb-style mixing, making the set highly predictable.
Six tools is well-scoped for an OIDC4VCI issuance server, covering offer inspection, metadata, flow analysis, initiation, status, and credential request. Each tool earns its place with no redundant or superfluous additions.
The toolset covers the pre-authorized code issuance path well, but the authorization-code grant is left in waiting_for_user_authorization with no tool to complete the user-authorization redirect or exchange the authorization code. This is a notable dead end for standard OIDC4VCI authorization-code flows.
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