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agentseal-mcp

servidor MCP agentseal-mcp

Servidor MCP para AgentSeal. Registros de auditoría a prueba de manipulaciones para agentes de IA, utilizando cadenas de hash SHA-256.

Cada acción del agente se registra en una cadena de hash. Con esto, puedes demostrar realmente a tus clientes que tu agente hizo lo que dijo que hizo.

Configuración

Claude Desktop

Añade a tu claude_desktop_config.json:

{
  "mcpServers": {
    "agentseal": {
      "command": "npx",
      "args": ["-y", "agentseal-mcp"],
      "env": {
        "AGENTSEAL_API_KEY": "as_sk_your_key_here"
      }
    }
  }
}

Reinicia Claude Desktop después de guardar.

Cursor / Otros hosts MCP

La misma configuración: añade el servidor con tu clave API.

Variables de entorno

Variable

Requerido

Descripción

AGENTSEAL_API_KEY

Tu clave API de agentseal.io

AGENTSEAL_URL

No

URL base de API personalizada (por defecto a producción)

Related MCP server: PiQrypt MCP Server

Herramientas

record_action

Registra una acción del agente en el registro de auditoría. Llama a esto después de acciones significativas para crear un registro encadenado criptográficamente de lo que sucedió y por qué.

Parámetro

Tipo

Requerido

Descripción

agent_id

string

Identificador del agente (ej. research-bot)

action_type

string

Qué tipo de acción (ej. email:send, file:write, api:call)

action_params

object

No

Detalles de la acción

reasoning

string

No

Por qué el agente decidió realizar esta acción

authorized_by

string

No

Quién o qué aprobó la acción

Devuelve un número de secuencia y un hash SHA-256 que confirma que la entrada fue encadenada.

query_actions

Busca acciones registradas previamente en el registro de auditoría. Úsalo para comprobar qué acciones se han tomado o recordar decisiones pasadas.

Parámetro

Tipo

Requerido

Descripción

agent_id

string

No

Filtrar por agente

action_type

string

No

Filtrar por tipo de acción

limit

number

No

Máximo de entradas a devolver (por defecto 20)

verify_chain

Verifica la integridad de la cadena de hash. El hash SHA-256 de cada entrada incluye el hash de la entrada anterior; si se modificó algún registro, la cadena se rompe y esto informa dónde.

Parámetro

Tipo

Requerido

Descripción

agent_id

string

No

Verifica la cadena para un agente específico. Si se omite, verifica todas las entradas.

Devuelve el número de entradas verificadas y si la cadena está intacta.

Cómo funciona

Cada acción registrada se cifra con SHA-256. Ese hash incluye el hash de la entrada anterior, formando una cadena. Modifica cualquier registro y cada hash posterior cambiará: verify_chain lo detecta al instante.

Obtener una clave API

Regístrate en agentseal.io. De uso gratuito.

SDK de Python

Para integración directa sin MCP: pip install agentseal-sdk. Consulta agentseal-sdk.

Licencia

MIT

Available Tools

3 tools
query_actionsA

Look up previously recorded actions from the audit trail. Use this to check what actions have been taken, verify history, or recall past decisions.

ParametersJSON Schema
NameRequiredDescriptionDefault
agent_idNoFilter by agent ID
action_typeNoFilter by action type
limitNoMax entries to return (default 20)

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description carries the burden. It implies read-only behavior by saying 'look up', but does not explicitly state non-destructiveness, side effects, or permissions needed. It is adequate but could be more explicit.

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 succinct sentences, front-loaded with the main purpose, no redundant information. Every sentence adds value.

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 the simplicity (3 optional parameters, no output schema), the description covers the main use. However, it omits details about the return format, which could aid agent understanding. Still, it is mostly 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%, so baseline is 3. The description does not add any extra meaning beyond what the schema already provides for each parameter. It is sufficient but not enhanced.

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 'look up' and the resource 'previously recorded actions from the audit trail'. It also lists use cases: 'check what actions have been taken, verify history, or recall past decisions'. This distinguishes it from siblings like record_action (write) and verify_chain.

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 (check actions, verify history, recall decisions). However, it does not explicitly mention when not to use it or compare to alternatives, though siblings are distinct enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

record_actionA

Record an agent action to the AgentSeal audit hash trail. Call this after every significant action (sending emails, modifying files, running queries, making API calls) to create a cryptographically sealed record of what happened and why.

ParametersJSON Schema
NameRequiredDescriptionDefault
agent_idYesIdentifier for this agent (e.g. 'research-bot', 'finance-agent')
action_typeYesWhat type of action was taken (e.g. 'email:send', 'file:write', 'api:call', 'db:query')
action_paramsNoParameters of the action (e.g. {to: 'user@example.com', subject: '...'})
reasoningNoWhy you decided to take this action — your chain of thought
authorized_byNoWho or what authorized this action (e.g. 'user:alice', 'policy:auto-approve')

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, description carries full burden. Mentions 'cryptographically sealed record' hinting at immutability, but does not disclose side effects, permanence, or system impact. Adequate for a simple append action, but could be more detailed.

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 efficiently convey purpose and usage. No extraneous information; every word adds value.

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 the tool's complexity (5 params, nested objects, no output schema), the description covers purpose and usage well but omits mention of return value or additional behavioral context. Nearly 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%, so baseline 3. Description does not add extra parameter meaning beyond the schema; all parameters are already well-described in 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 clearly states the tool records actions to an audit trail, with specific verb 'Record' and resource 'agent action'. It distinguishes from siblings (query_actions, verify_chain) by focusing on recording, not querying or verifying.

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 advises calling 'after every significant action' with examples, providing strong when-to-use guidance. Lacks explicit when-not-to-use instructions but context with sibling tools implies alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

verify_chainA

Verify the integrity of the audit trail hash chain. Each entry's SHA-256 hash includes the previous entry's hash — if any record was modified, the chain breaks and this will report where.

ParametersJSON Schema
NameRequiredDescriptionDefault
agent_idNoVerify chain for a specific agent only. If omitted, verifies all entries.

TDQS

A4.2/5.0
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 the core behavior: verifies chain integrity, uses SHA-256, reports break location. However, it does not explicitly state whether the tool is read-only or has side effects, which is a minor gap.

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: two sentences that efficiently convey purpose, mechanism, and behavior. No redundant or unnecessary 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?

For a simple tool with one optional parameter and no output schema, the description covers the key aspects: what it verifies, how it works, and what indicates tampering. It could optionally detail the output format (e.g., break location), but this is not essential for correct 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?

The description does not mention the agent_id parameter directly. However, the input schema already describes it clearly (100% coverage). The description adds no additional meaning beyond the schema, so baseline score of 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's purpose: 'Verify the integrity of the audit trail hash chain.' It explains the cryptographic mechanism (SHA-256 hash chain) and distinguishes itself from sibling tools (query_actions, record_action) by focusing exclusively on integrity verification.

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 implicitly tells when to use this tool: when you need to detect data tampering via hash chain breaks. It does not explicitly state alternatives or when not to use, but the purpose is clear enough that an agent can infer appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 3 tool updatesv0.1.0
    • First observedquery_actions
    • First observedrecord_action
    • First observedverify_chain

TDQS

A4.4/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: record_action records, query_actions retrieves, verify_chain checks integrity. No overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (query_actions, record_action, verify_chain), making them predictable and easy to understand.

Tool Count5/5

Three tools is an ideal scope for an audit trail server, covering the essential operations of recording, querying, and verifying without unnecessary bloat.

Completeness5/5

The tool surface fully covers the core lifecycle of an audit trail: recording actions, looking up history, and verifying chain integrity. No obvious gaps given the domain's immutability requirements.

Maintenance

ActivityInactive
ResponsivenessNo issues

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