AgentSeal 的 MCP 服务器。使用 SHA-256 哈希链为 AI Agent 提供防篡改审计日志。
每个 Agent 的操作都记录在哈希链中。有了它，您可以向客户证明您的 Agent 确实执行了其声称的操作。
添加到您的 claude_desktop_config.json：
{
"mcpServers": {
"agentseal": {
"command": "npx",
"args": ["-y", "agentseal-mcp"],
"env": {
"AGENTSEAL_API_KEY": "as_sk_your_key_here"
}
}
}
}保存后重启 Claude Desktop。
配置相同 — 使用您的 API 密钥添加服务器。
变量 | 必需 | 描述 |
| 是 | 您从 agentseal.io 获取的 API 密钥 |
| 否 | 自定义 API 基础 URL（默认为生产环境） |
Related MCP server: PiQrypt MCP Server
record_action将 Agent 操作记录到审计追踪中。在执行重要操作后调用此工具，以创建关于操作内容和原因的加密链式记录。
参数 | 类型 | 必需 | 描述 |
| string | 是 | Agent 的标识符（例如 |
| string | 是 | 操作类型（例如 |
| object | 否 | 操作详情 |
| string | 否 | Agent 决定执行此操作的原因 |
| string | 否 | 谁或什么批准了该操作 |
返回序列号和 SHA-256 哈希值，确认条目已链接。
query_actions从审计追踪中查找之前记录的操作。使用此工具检查已执行的操作或回顾过去的决策。
参数 | 类型 | 必需 | 描述 |
| string | 否 | 按 Agent 筛选 |
| string | 否 | 按操作类型筛选 |
| number | 否 | 返回的最大条目数（默认为 20） |
verify_chain验证哈希链的完整性。每个条目的 SHA-256 哈希都包含前一个条目的哈希值——如果任何记录被修改，链条就会断裂，此工具会报告断裂位置。
参数 | 类型 | 必需 | 描述 |
| string | 否 | 验证特定 Agent 的链。如果省略，则验证所有条目。 |
返回已验证的条目数量以及链条是否完整。
每个记录的操作都使用 SHA-256 进行哈希处理。该哈希值包含前一个条目的哈希值，从而形成一条链。修改任何记录，其后的所有哈希值都会改变——verify_chain 会立即检测到。
在 agentseal.io 注册。免费使用。
如需在不使用 MCP 的情况下直接集成：pip install agentseal-sdk。请参阅 agentseal-sdk。
MIT
Look up previously recorded actions from the audit trail. Use this to check what actions have been taken, verify history, or recall past decisions.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | No | Filter by agent ID | |
| action_type | No | Filter by action type | |
| limit | No | Max entries to return (default 20) |
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.
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.
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.
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.
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.
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 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.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes | Identifier for this agent (e.g. 'research-bot', 'finance-agent') | |
| action_type | Yes | What type of action was taken (e.g. 'email:send', 'file:write', 'api:call', 'db:query') | |
| action_params | No | Parameters of the action (e.g. {to: 'user@example.com', subject: '...'}) | |
| reasoning | No | Why you decided to take this action — your chain of thought | |
| authorized_by | No | Who or what authorized this action (e.g. 'user:alice', 'policy:auto-approve') |
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.
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.
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.
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.
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.
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 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.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | No | Verify chain for a specific agent only. If omitted, verifies all entries. |
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.
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.
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.
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.
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.
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.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0query_actionsrecord_actionverify_chainScored across 3 tools
Each tool has a clearly distinct purpose: record_action records, query_actions retrieves, verify_chain checks integrity. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern (query_actions, record_action, verify_chain), making them predictable and easy to understand.
Three tools is an ideal scope for an audit trail server, covering the essential operations of recording, querying, and verifying without unnecessary bloat.
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.
Bitcoin-anchored, tamper-evident audit log for AI agents — record, disclose and verify actions.
Issue & verify signed (ed25519), hash-chained, timestamped provenance receipts for agent actions.
Immutable event logging and audit trail for agent transactions
Tamper-evident proof creation and verification for AI agents via MCP, A2A, and REST.
