mcp-evidence-ledger
An MCP server providing an append-only, hash-chained evidence ledger for agent actions, where every record is a tamper-evident receipt cryptographically bound to all prior records and persisted as human-readable JSONL local state. It exposes tools to append records, verify chain integrity (pinpointing tampering), query records by actor/action/target/time, and fetch ledger stats—with no update or delete capabilities by design.
README
mcp-evidence-ledger
An MCP server providing an append-only, hash-chained evidence ledger for agent actions. Every record is a tamper-evident receipt cryptographically bound to all prior records, persisted as human-readable local state. Deterministic, no LLM. Agents are non-deterministic; their audit trail should not be.
The idea
When an autonomous agent acts, you need a record of what it did that cannot be quietly altered afterward. This is that record: an append-only ledger where each entry's hash is computed over the previous entry's hash, forming a chain. Altering any past record breaks every hash after it, so tampering is not just discouraged -- it is detectable, and the exact altered record can be named.
It runs as an MCP server, so any agent can call it as a tool. The evidence lands in a plain JSONL file you can open and read: a complete, ordered, cryptographically linked account of every action.
Why it is built this way
Hash-chained, like a mini ledger. record_hash = SHA256(prev_hash + canonical_body). The chain is the integrity guarantee. See ADR 0001.
Append-only, enforced by absence. The server exposes append, read, verify -- and deliberately no update and no delete. History can be written and read, never rewritten. See ADR 0002.
Real, human-readable local state. The ledger is JSONL, one record per line, chosen over a binary store so you can cat your own audit trail. If someone edits the file directly, verify catches it -- which is the point.
Deterministic. No LLM anywhere. Hashing, chaining, and verification are pure functions of the records. Nothing here is probabilistic. An evidence ledger that could be talked out of a finding would not be evidence.
Prove it yourself
Two runnable demos write real ledgers you can inspect:
uv run python specs/demo_basic.py # record agent actions, verify the chain
uv run python specs/demo_tamper.py # edit a record in the file, watch verify catch it
demo_tamper.py writes a clean ledger, changes an access level from read to admin directly in the file, and shows the verifier pinpointing the tampered record. Tamper-evidence, demonstrated rather than asserted.
Run as an MCP server
uv sync --extra mcp
EVIDENCE_LEDGER_PATH=./evidence.ledger.jsonl uv run python -m ledger.server
The operator sets the ledger path via EVIDENCE_LEDGER_PATH, not the calling agent -- the agent writes evidence, it does not choose where evidence lands.
MCP tools
| Tool | What it does |
|---|---|
append_record |
Record an action, receive a tamper-evident receipt hash |
verify_ledger |
Re-walk the chain; prove integrity or pinpoint the first break |
get_record |
Fetch one record by sequence |
query_ledger |
Filter by actor, action, target, or time range |
ledger_stats |
Counts, head hash, and a live integrity check |
There is no update tool and no delete tool. That is deliberate.
CLI (for humans)
uv run evidence-ledger --path ./evidence.ledger.jsonl append deploy-agent deploy payments-api --details '{"version":"4.2.0"}'
uv run evidence-ledger --path ./evidence.ledger.jsonl verify
uv run evidence-ledger --path ./evidence.ledger.jsonl stats
What a record contains
The agent supplies the semantics (actor, action, target, details). The ledger owns the integrity fields (seq, timestamp, prev_hash, record_hash) -- an agent cannot forge a hash or a sequence number, because it never computes them.
Optional: a governance lens
The core is generic -- any actor, any action. An optional layer maps actions onto the governance failure taxonomy shared across the portfolio (deployment authorization, change management, data governance, and so on), so an evidence ledger can be read through a governance lens without the core depending on it.
Related work
| Repo | Relationship |
|---|---|
| mcp-governance-gateway | Enforces governance on the write path; this records tamper-evident proof of what happened |
| ai-governance-framework | The replay imperative this ledger operationalizes |
Design decisions
License
Apache 2.0
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.