actionlog
actionlog
Tamper-Evident Autonomous Agent Action Audit & Governance Logging MCP Server. Designed for AI agent compliance, recording irreversible audit trails and verifying tool execution integrity.
Features
Cryptographic Audit Chain: Every agent action, tool invocation, and API execution is hashed into a tamper-evident sequential log.
Agent Governance & Compliance: Built for enterprise AI requirements (SOC2, EU AI Act traceability, agent liability auditing).
Model Context Protocol (MCP): Native integration for Claude Desktop, Cursor, and multi-agent orchestrators.
Related MCP server: QuantaOptima
Quick Start
Direct Execution
npx actionlogClaude Desktop Integration
Add to your claude_desktop_config.json:
{
"mcpServers": {
"actionlog": {
"command": "npx",
"args": ["-y", "actionlog"]
}
}
}Tools Included
record_agent_action: Commits an agent action into the cryptographic hash chain.verify_log_integrity: Validates historical log entries against checksum tampering.
License
MIT © tudadada
Available Tools
2 toolsrecord_agent_actionB
Records an autonomous agent decision or tool execution with cryptographic integrity hash.
| Name | Required | Description | Default |
|---|---|---|---|
| payload | Yes | JSON string containing execution parameters or outcome | |
| agent_id | Yes | Unique identifier of the executing agent | |
| action_type | Yes | Action category (e.g., tool_call, transaction, file_write, api_dispatch) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'cryptographic integrity hash' but does not explain side effects such as immutability, storage, or failure modes. It also does not state whether the record is append-only or how the hash is used, leaving significant gaps for a tool that likely affects audit trails.
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 sentence with zero waste, front-loading the core purpose and the key differentiator (integrity hash). It is concise and to the point.
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 three fully documented required parameters and no output schema, the description is minimally sufficient. However, it lacks any mention of the sibling verify_log_integrity or when to use this tool for recording versus verifying, which would improve completeness. The absence of behavioral details beyond the hash also leaves some ambiguity.
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 100%, so all three parameters are documented in the schema. The description adds no extra meaning beyond what the schema provides, such as examples or constraints on the payload format. Since the schema already does the heavy lifting, a baseline 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 verb 'records' and the resource 'autonomous agent decision or tool execution', and adds the distinctive feature of a cryptographic integrity hash, which differentiates it from the sibling verify_log_integrity. An agent can immediately understand the core function.
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?
No explicit guidance is given on when to use this tool versus the sibling verify_log_integrity. The description does not mention the alternative or any conditions for selection, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_log_integrityA
Audits sequential cryptographic checksums to ensure audit log has not been altered.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes | Agent ID whose action log history will be verified | |
| audit_depth | No | Number of recent log events to verify (default 50) |
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 of behavioral disclosure. It mentions the method (cryptographic checksums) but does not state whether the operation is read-only, what happens on verification failure, or any side effects. For a verification tool, this is a significant gap that leaves the agent guessing about the result format and error behavior.
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?
A single, tightly written sentence that front-loads the core verb and purpose. No redundant words or filler.
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 two-parameter tool, the description is adequate in scope, but because there is no output schema, the description should clarify what the tool returns (e.g., a boolean, a report, or an error) and whether it is safe to call repeatedly. This omission makes it slightly incomplete for an agent deciding how to handle the result.
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 100%, so both parameters (agent_id and audit_depth) are already documented in the input schema. The tool description adds no additional meaning about parameters, so the baseline of 3 applies.
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?
States a specific verb (audits) and resource (audit log) with a clear intent (ensure not altered). It is unambiguously distinct from the sibling 'record_agent_action', which writes entries rather than verifying them, so an agent can tell them apart immediately.
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?
Provides clear context for when to use the tool (verifying log integrity) and implicitly that it is for verification, not recording. However, it does not explicitly name the sibling or give when-not conditions, so it falls short of a full 5.
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.
2 tool updates
v1.0.0- First observed
record_agent_action - First observed
verify_log_integrity
TDQS
Scored across 2 tools
The two tools have completely distinct purposes: one appends an action to the log, the other verifies the log's integrity. There is no overlap or ambiguity in their intended usage.
Both tool names follow the same verb_noun pattern (record_agent_action, verify_log_integrity), are in snake_case, and clearly communicate the action and target. The naming is fully consistent.
With only two tools, the server feels thin even for a focused audit-logging purpose. While the count is not excessive, it falls at the low end where a single extra tool for retrieval would make the set feel more complete.
The server covers the core record and verify capabilities, but there is no way to read, list, or query the logged actions. This creates a notable gap: an agent can write and validate entries but cannot retrieve them for normal use.
Maintenance
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