Audit Ledger MCP

Record AI decisions to a tamper-evident audit ledger from any MCP-compatible agent.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "audit-ledger-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "audit-ledger-mcp"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Documentation Overview

audit-ledger-mcp

Connect Claude, Cursor, LangGraph, or your own agent to the AI Audit Ledger. This MCP server gives an agent the tools to record, check, and list decisions in a tamper-evident log with one line of config.

It is built for teams that need a clear record of AI decisions: EU AI Act Article 12 logging, FCA SS1/23 model risk evidence, and GDPR data minimisation. Raw personal data is hashed locally before anything is sent, so the ledger only sees fingerprints.

The AI Audit Ledger family. This MCP server writes decisions to the ledger, which proves what happened and whether the record was changed. The AI Decision Evidence Hub sits above the ledger, read-only. It turns each lightweight decision record into an audit case file by showing what evidence is present, what is still missing, who owns each gap, and the current readiness score. Family: audit-ledger · audit-ledger-mcp · evidence-hub.

Try the live dashboard → · 30 synthetic decisions written via this MCP server, queryable and verifiable.

LangGraph agents using audit-ledger-mcp — triage, risk, and human-in-the-loop each calling record_decision

A LangGraph workflow calls record_decision after each agent step. Three audit events written to the live ledger; every one independently verifiable.

What it does

Exposes four tools to any MCP-compatible agent:

Tool	What it does
`record_decision`	Log an AI decision. Hashes inputs locally, then writes through to the ledger. Returns an event ID.
`verify_decision`	Cross-check a stored record against the immutable S3 Object Lock copy. Returns `integrity_verified: true/false`.
`verify_completeness`	Detect deleted or missing records. Compares the ledger's per-tenant counter against the rows actually present and returns any sequence numbers that are gone. The answer to "can you prove the log is complete?"
`list_decisions`	Query recent decisions, optionally filtered by time window. Tenant-scoped by API key.

Each call ends up as a regulator-grade audit record in your deployed ledger — DynamoDB for query, S3 Object Lock COMPLIANCE mode for the immutable copy, 7-year retention by default.

Quick start — zero configuration

Terminal

npx -y audit-ledger-mcp

That's it. With no environment variables, the server boots into sandbox mode and writes records to a shared public tenant on a hosted ledger. You can try every tool — record_decision, verify_decision, verify_completeness, list_decisions — without provisioning anything.

When sandbox mode is active, you'll see a banner on stderr:

Code

[audit-ledger-mcp] ─────────────── SANDBOX MODE ───────────────
[audit-ledger-mcp] No AUDIT_API_URL configured.
[audit-ledger-mcp] Using the public sandbox at sandbox-public.
[audit-ledger-mcp]   View: https://d2pfirb2397ixy.cloudfront.net
[audit-ledger-mcp] Do NOT write real personal data...

Sandbox properties


Hosted by	github.com/shahidh68/audit-ledger (same AWS deployment)
Tenant	`sandbox-public` (shared, public)
Rate limit	100 requests/minute per IP
Retention	7 years (records cannot be deleted)
Audience	Tyre-kickers, integration tests, framework demos
NOT for	Production data, customer PII, real compliance records

Wire it into Claude Desktop with zero config

config.json

{
  "mcpServers": {
    "audit-ledger-sandbox": {
      "command": "npx",
      "args": ["-y", "audit-ledger-mcp"]
    }
  }
}

Restart Claude Desktop. The four tools appear in the MCP menu immediately. Try asking Claude to "record this decision: should X be approved?" and watch a record land in the sandbox dashboard.

Production install

For real workloads, deploy your own audit ledger and point the MCP server at it:

Terminal

npm install -g audit-ledger-mcp

Configure with the API URL plus your tenant keys (any of them being set switches off sandbox mode). AUDIT_HMAC_KEY is technically optional for backwards compatibility but strongly recommended — see the note above the value below:

server.ts

export AUDIT_API_URL="https://<api-id>.execute-api.<region>.amazonaws.com/prod"
export AUDIT_WRITE_KEY="<your-tenant-write-key>"
export AUDIT_READ_KEY="<your-tenant-read-key>"

# Strongly recommended. Tenant-held secret used to HMAC PII and prompts
# locally before sending. Generate once, store next to AUDIT_WRITE_KEY:
#   node -e "console.log(require('crypto').randomBytes(32).toString('hex'))"
# If unset, the MCP falls back to plain SHA-256 and warns once (back-compat).
export AUDIT_HMAC_KEY="<your-tenant-hmac-secret>"

# Optional
export AUDIT_TIMEOUT_MS=5000        # default 5000
export AUDIT_RETRY_ATTEMPTS=3       # default 3

The full template lives in .env.example.

Wire it into an agent

Claude Desktop

Edit your claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json, Windows: %APPDATA%\Claude\claude_desktop_config.json):

config.json

{
  "mcpServers": {
    "audit-ledger": {
      "command": "npx",
      "args": ["-y", "audit-ledger-mcp"],
      "env": {
        "AUDIT_API_URL": "https://<api-id>.execute-api.<region>.amazonaws.com/prod",
        "AUDIT_WRITE_KEY": "<your-tenant-write-key>",
        "AUDIT_READ_KEY": "<your-tenant-read-key>",
        "AUDIT_HMAC_KEY": "<your-tenant-hmac-secret>"
      }
    }
  }
}

AUDIT_HMAC_KEY is the tenant secret used to keyed-hash PII locally before any payload leaves the MCP server process. Generate it once with node -e "console.log(require('crypto').randomBytes(32).toString('hex'))" and store the result in the env block above. The MCP never transmits this value, only reads it.

Restart Claude Desktop. You'll see "audit-ledger" in the MCP tools menu. Ask Claude something like "Record this decision: I declined the application because…" and watch it call record_decision automatically.

Cursor

In Cursor settings → MCP → add server:

config.json

{
  "mcpServers": {
    "audit-ledger": {
      "command": "npx",
      "args": ["-y", "audit-ledger-mcp"],
      "env": {
        "AUDIT_API_URL": "https://<api-id>.execute-api.<region>.amazonaws.com/prod",
        "AUDIT_WRITE_KEY": "<your-tenant-write-key>",
        "AUDIT_READ_KEY": "<your-tenant-read-key>",
        "AUDIT_HMAC_KEY": "<your-tenant-hmac-secret>"
      }
    }
  }
}

LangGraph (Python)

Using langchain-mcp-adapters:

server.ts

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_anthropic import ChatAnthropic
import os

client = MultiServerMCPClient({
    "audit-ledger": {
        "command": "npx",
        "args": ["-y", "audit-ledger-mcp"],
        "transport": "stdio",
        "env": {
            "AUDIT_API_URL":   os.environ["AUDIT_API_URL"],
            "AUDIT_WRITE_KEY": os.environ["AUDIT_WRITE_KEY"],
            "AUDIT_READ_KEY":  os.environ["AUDIT_READ_KEY"],
            "AUDIT_HMAC_KEY":  os.environ["AUDIT_HMAC_KEY"],
        },
    }
})

tools = await client.get_tools()
agent = create_react_agent(
    ChatAnthropic(model="claude-sonnet-4-7-20251022"),
    tools,
)

# The agent can now call record_decision, verify_decision, verify_completeness, list_decisions
result = await agent.ainvoke({
    "messages": [{"role": "user", "content": "Triage this loan application…"}]
})

Custom client (raw MCP)

bash

AUDIT_API_URL=... AUDIT_WRITE_KEY=... AUDIT_READ_KEY=... AUDIT_HMAC_KEY=... npx -y audit-ledger-mcp

The server speaks MCP over stdio. Send initialize, tools/list, and tools/call requests per the MCP specification.

How a `record_decision` call flows

Code

Agent                  audit-ledger-mcp                  AWS (your ledger)
  |                          |                                 |
  |--- record_decision ----->|                                 |
  |   raw_user_input         | (hash locally — no PII over     |
  |   raw_system_prompt      |  the wire from this point)      |
  |   decision_output        |                                 |
  |   human_in_loop          |                                 |
  |                          |--- HTTPS POST /audit/events --->|
  |                          |    {hashes + decision +         |
  |                          |     x-api-key}                  |
  |                          |                                 |
  |                          |<--- 202 Accepted ---------------|
  |                          |    { event_id, ... }            |
  |<--- event_id ------------|                                 |
  |     recorded_at          |                                 |
  |     note                 |                                 |

Storage on the AWS side happens asynchronously through SQS → Processor Lambda → DynamoDB + S3 Object Lock. See the main repo's ARCHITECTURE.md for the full path.

Tool reference

`record_decision`

Record an AI decision to the ledger.

Read the full README →View source on GitHub →

Related MCP Servers

View all in Developer Tools View all alternatives

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Audit Ledger MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "audit-ledger-mcp": { "command": "npx", "args": ["-y", "audit-ledger-mcp"] } }

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Technical Specs & Signals

CategoryDeveloper Tools

27Quality signal: Emerging · 27/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20

Documentation & tools11/30

Adoption & activity1/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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More in 💻 Developer Tools →Best MCP servers for Developers →Alternatives to Audit Ledger MCP →Install in Claude Desktop Install in Cursor Install in VS Code

Audit Ledger MCP

Record AI decisions to a tamper-evident audit ledger from any MCP-compatible agent.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "audit-ledger-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "audit-ledger-mcp"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Documentation Overview

audit-ledger-mcp

The AI Audit Ledger family. This MCP server writes decisions to the ledger, which proves what happened and whether the record was changed. The AI Decision Evidence Hub sits above the ledger, read-only. It turns each lightweight decision record into an audit case file by showing what evidence is present, what is still missing, who owns each gap, and the current readiness score. Family: audit-ledger · audit-ledger-mcp · evidence-hub.

Try the live dashboard → · 30 synthetic decisions written via this MCP server, queryable and verifiable.

LangGraph agents using audit-ledger-mcp — triage, risk, and human-in-the-loop each calling record_decision

A LangGraph workflow calls record_decision after each agent step. Three audit events written to the live ledger; every one independently verifiable.

What it does

Exposes four tools to any MCP-compatible agent:

Tool	What it does
`record_decision`	Log an AI decision. Hashes inputs locally, then writes through to the ledger. Returns an event ID.
`verify_decision`	Cross-check a stored record against the immutable S3 Object Lock copy. Returns `integrity_verified: true/false`.
`verify_completeness`	Detect deleted or missing records. Compares the ledger's per-tenant counter against the rows actually present and returns any sequence numbers that are gone. The answer to "can you prove the log is complete?"
`list_decisions`	Query recent decisions, optionally filtered by time window. Tenant-scoped by API key.

Each call ends up as a regulator-grade audit record in your deployed ledger — DynamoDB for query, S3 Object Lock COMPLIANCE mode for the immutable copy, 7-year retention by default.

Quick start — zero configuration

Terminal

npx -y audit-ledger-mcp

When sandbox mode is active, you'll see a banner on stderr:

Code

[audit-ledger-mcp] ─────────────── SANDBOX MODE ───────────────
[audit-ledger-mcp] No AUDIT_API_URL configured.
[audit-ledger-mcp] Using the public sandbox at sandbox-public.
[audit-ledger-mcp]   View: https://d2pfirb2397ixy.cloudfront.net
[audit-ledger-mcp] Do NOT write real personal data...

Sandbox properties


Hosted by	github.com/shahidh68/audit-ledger (same AWS deployment)
Tenant	`sandbox-public` (shared, public)
Rate limit	100 requests/minute per IP
Retention	7 years (records cannot be deleted)
Audience	Tyre-kickers, integration tests, framework demos
NOT for	Production data, customer PII, real compliance records

Wire it into Claude Desktop with zero config

config.json

{
  "mcpServers": {
    "audit-ledger-sandbox": {
      "command": "npx",
      "args": ["-y", "audit-ledger-mcp"]
    }
  }
}

Restart Claude Desktop. The four tools appear in the MCP menu immediately. Try asking Claude to "record this decision: should X be approved?" and watch a record land in the sandbox dashboard.

Production install

For real workloads, deploy your own audit ledger and point the MCP server at it:

Terminal

npm install -g audit-ledger-mcp

server.ts

export AUDIT_API_URL="https://<api-id>.execute-api.<region>.amazonaws.com/prod"
export AUDIT_WRITE_KEY="<your-tenant-write-key>"
export AUDIT_READ_KEY="<your-tenant-read-key>"

# Strongly recommended. Tenant-held secret used to HMAC PII and prompts
# locally before sending. Generate once, store next to AUDIT_WRITE_KEY:
#   node -e "console.log(require('crypto').randomBytes(32).toString('hex'))"
# If unset, the MCP falls back to plain SHA-256 and warns once (back-compat).
export AUDIT_HMAC_KEY="<your-tenant-hmac-secret>"

# Optional
export AUDIT_TIMEOUT_MS=5000        # default 5000
export AUDIT_RETRY_ATTEMPTS=3       # default 3

The full template lives in .env.example.

Wire it into an agent

Claude Desktop

Edit your claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json, Windows: %APPDATA%\Claude\claude_desktop_config.json):

config.json

{
  "mcpServers": {
    "audit-ledger": {
      "command": "npx",
      "args": ["-y", "audit-ledger-mcp"],
      "env": {
        "AUDIT_API_URL": "https://<api-id>.execute-api.<region>.amazonaws.com/prod",
        "AUDIT_WRITE_KEY": "<your-tenant-write-key>",
        "AUDIT_READ_KEY": "<your-tenant-read-key>",
        "AUDIT_HMAC_KEY": "<your-tenant-hmac-secret>"
      }
    }
  }
}

Cursor

In Cursor settings → MCP → add server:

config.json

{
  "mcpServers": {
    "audit-ledger": {
      "command": "npx",
      "args": ["-y", "audit-ledger-mcp"],
      "env": {
        "AUDIT_API_URL": "https://<api-id>.execute-api.<region>.amazonaws.com/prod",
        "AUDIT_WRITE_KEY": "<your-tenant-write-key>",
        "AUDIT_READ_KEY": "<your-tenant-read-key>",
        "AUDIT_HMAC_KEY": "<your-tenant-hmac-secret>"
      }
    }
  }
}

LangGraph (Python)

Using langchain-mcp-adapters:

server.ts

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_anthropic import ChatAnthropic
import os

client = MultiServerMCPClient({
    "audit-ledger": {
        "command": "npx",
        "args": ["-y", "audit-ledger-mcp"],
        "transport": "stdio",
        "env": {
            "AUDIT_API_URL":   os.environ["AUDIT_API_URL"],
            "AUDIT_WRITE_KEY": os.environ["AUDIT_WRITE_KEY"],
            "AUDIT_READ_KEY":  os.environ["AUDIT_READ_KEY"],
            "AUDIT_HMAC_KEY":  os.environ["AUDIT_HMAC_KEY"],
        },
    }
})

tools = await client.get_tools()
agent = create_react_agent(
    ChatAnthropic(model="claude-sonnet-4-7-20251022"),
    tools,
)

# The agent can now call record_decision, verify_decision, verify_completeness, list_decisions
result = await agent.ainvoke({
    "messages": [{"role": "user", "content": "Triage this loan application…"}]
})

Custom client (raw MCP)

bash

AUDIT_API_URL=... AUDIT_WRITE_KEY=... AUDIT_READ_KEY=... AUDIT_HMAC_KEY=... npx -y audit-ledger-mcp

The server speaks MCP over stdio. Send initialize, tools/list, and tools/call requests per the MCP specification.

How a `record_decision` call flows

Code

Agent                  audit-ledger-mcp                  AWS (your ledger)
  |                          |                                 |
  |--- record_decision ----->|                                 |
  |   raw_user_input         | (hash locally — no PII over     |
  |   raw_system_prompt      |  the wire from this point)      |
  |   decision_output        |                                 |
  |   human_in_loop          |                                 |
  |                          |--- HTTPS POST /audit/events --->|
  |                          |    {hashes + decision +         |
  |                          |     x-api-key}                  |
  |                          |                                 |
  |                          |<--- 202 Accepted ---------------|
  |                          |    { event_id, ... }            |
  |<--- event_id ------------|                                 |
  |     recorded_at          |                                 |
  |     note                 |                                 |

Storage on the AWS side happens asynchronously through SQS → Processor Lambda → DynamoDB + S3 Object Lock. See the main repo's ARCHITECTURE.md for the full path.

Tool reference

`record_decision`

Record an AI decision to the ledger.

Read the full README →View source on GitHub →

Related MCP Servers

View all in Developer Tools View all alternatives

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Audit Ledger MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "audit-ledger-mcp": { "command": "npx", "args": ["-y", "audit-ledger-mcp"] } }

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Technical Specs & Signals

CategoryDeveloper Tools

27Quality signal: Emerging · 27/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20

Documentation & tools11/30

Adoption & activity1/15

Community engagement0/10

★ Spotlight Slot

Feature Your MCP Server

Get maximum visibility for your server across our directory, search results, and detail pages.

Spotlight Your Server

Own this project?

Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

Claim & get free dofollow

Share & Embed

Add our SVG badge (dark/light directory styles) or embeddable widget to your site.

Explore more

More in 💻 Developer Tools →Best MCP servers for Developers →Alternatives to Audit Ledger MCP →Install in Claude Desktop Install in Cursor Install in VS Code

Audit Ledger MCP

Quick Install

Client Config & Setup

Documentation Overview

audit-ledger-mcp

What it does

Quick start — zero configuration

Sandbox properties

Wire it into Claude Desktop with zero config

Production install

Wire it into an agent

Claude Desktop

Cursor

LangGraph (Python)

Custom client (raw MCP)

How a record_decision call flows

Tool reference

record_decision

Related MCP Servers

Reviews

Frequently Asked Questions about Audit Ledger MCP

AllMCPs Directory Badge

Technical Specs & Signals

Feature Your MCP Server

Own this project?

Share & Embed

Explore more

Audit Ledger MCP

Quick Install

Client Config & Setup

Documentation Overview

audit-ledger-mcp

What it does

Quick start — zero configuration

Sandbox properties

Wire it into Claude Desktop with zero config

Production install

Wire it into an agent

Claude Desktop

Cursor

LangGraph (Python)

Custom client (raw MCP)

How a record_decision call flows

Tool reference

record_decision

Related MCP Servers

Reviews

Frequently Asked Questions about Audit Ledger MCP

AllMCPs Directory Badge

Technical Specs & Signals

Feature Your MCP Server

Own this project?

Share & Embed

Explore more

How a `record_decision` call flows

`record_decision`

How a `record_decision` call flows

`record_decision`