About evidence-gate
evidence-gate is a local, deterministic toolkit for teams checking artifacts, claim evidence, and completion requirements before releasing AI-generated work. It includes two MCP servers and six Agent Skills, with no model calls, file uploads, or network access.
Key features
- 01Check retained files and path boundaries
- 02Audit claim evidence and literal citations
- 03Evaluate completion contracts and blockers
- 04Produce structured statuses and receipts
- 05Provide six portable Agent Skills
Use cases
- 01Check required artifacts before release
- 02Review claim evidence and quoted text
- 03Track unmet requirements and blockers
- 04Create a scoped release receipt
MCP support
The toolkit includes Evidence Gate and Release Gate, two MCP servers using stdio and providing eight tools for local artifacts, declared evidence, citation containment, completion contracts, and release receipts. They do not access the network or call models; receipts cover only their stated conditions and scope.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEDaily AI Agent Toolkit
Local, deterministic tools for checking AI-generated work before it is released.
The toolkit contains two Model Context Protocol (MCP) servers and six portable Agent Skills. They inspect retained artifacts, declared claim support, literal citations, completion contracts, blockers, and release receipts without calling a model, uploading files, or requiring a Daily AI Agents account.
Release status:
0.1.1patch release candidate. PyPI0.1.0is public; the patch corrects the case-sensitive MCP Registry ownership marker.
Why this exists
AI systems can produce convincing output without proving that required artifacts exist, cited text is present, or a completion contract was actually satisfied. These tools make those narrow checks repeatable and preserve uncertainty instead of silently upgrading it to success.
They deliberately do not determine broad truth, judge semantic entailment, approve a release, validate a live service, or establish legal or security compliance.
Included tools
| Component | Interface | Purpose |
|---|---|---|
| Evidence Gate | MCP server, four tools | Inspect artifacts, declared claim evidence, literal citation containment, and aggregate verification states. |
| Release Gate | MCP server, four tools | Check completion contracts, preserve requirement states, format blockers, and build retained release receipts. |
| Six Agent Skills | Portable skill directories | Reuse artifact, claim, contract, failure-state, and verification procedures with deterministic self-tests. |
Evidence Gate
verify_artifactaudit_claimsaudit_citationssummarize_verification
Release Gate
check_contractevaluate_completionformat_blockersbuild_release_receipt
Agent Skills
artifact-verifierclaim-truth-gatecompletion-contractcontract-checkerfail-loudverification-bench
Install and run
Python 3.11 or newer is required.
python -m pip install dailyaiagents-evidence-gate==0.1.1
python -m pip install dailyaiagents-release-gate==0.1.1
dailyai-evidence-gate --root /absolute/path/to/workspace
dailyai-release-gate --root /absolute/path/to/workspace
Until the packages are public, install from a clean checkout:
python -m pip install ./servers/evidence-gate ./servers/release-gate
Both servers use MCP stdio transport. A representative client configuration is:
{
"mcpServers": {
"dailyai-evidence-gate": {
"command": "dailyai-evidence-gate",
"args": ["--root", "/absolute/path/to/workspace"]
},
"dailyai-release-gate": {
"command": "dailyai-release-gate",
"args": ["--root", "/absolute/path/to/workspace"]
}
}
}
See client configuration for the supported transport boundary.
Reproduce the proof
Run the complete local gate:
bash scripts/test-all.sh
The release candidate includes:
- unit tests for both servers;
- deterministic self-tests for all six skills;
- 20 declared-outcome examples spanning all eight MCP tools;
- rooted-path and symlink-escape protections;
- clean-wheel installation and stdio tool-discovery checks;
- package-specific checksums, SBOMs, and build provenance.
See the examples, technical report, receipt schemas, release and recovery process, and local verification record. A passing local check proves only the condition and scope named in its receipt.
Architecture and security boundary
Live repository controls and current fail-closed publication gates are recorded in Repository controls.
MCP client
| stdio + structured inputs
v
Evidence Gate / Release Gate
| canonical path resolution beneath --root
v
Local retained files ---> structured status + scoped receipt
The servers do not use network access, telemetry, model inference, arbitrary shell execution, or hosted Daily AI Agents infrastructure. Inputs are treated as data rather than shell fragments. URL-only evidence remains UNVERIFIED, and literal citation containment is not semantic support.
Read SECURITY.md and the threat model before using the toolkit on sensitive work.
Project leadership
The toolkit was conceived and led by Cooper Reed, founder of Daily AI Agents LLC, with implementation, testing, release engineering, and documentation developed as a public engineering project. Public claims about the toolkit should link to reproducible checks or retained release evidence in this repository.
Contributing and support
Apache-2.0 licensed.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.