Skip to main content

digline-mcp

The MCP server for digline: it lets a coding agent read a digline result and measure a new one, and it does not let the agent promote a baseline.

Not because promotion is refused. Because there is no such tool.

The eight tools

tool what it does
list_runs every stored run of a suite, newest first, with the baseline marked
get_run one stored run — the verdicts, never the payload
get_baseline the approved reference, same shape
log which model answered, read down the stored runs; never a gate
compare a run against the baseline: did it get worse?
diff two runs, neither of them a reference: should I switch?
explain one run read back as typed facts, with the exit code
run execute the suite, with the call count acknowledged first

promote is absent by construction, and so are migrate, view and report. A baseline is an approved reference, and promote writes into .digline/<tenant>/baselines/, which is committed — anything landing there arrives in somebody's diff and must arrive because they put it there. A refusal would be a conversation an agent could argue with; an absence is not.

The reasoning is ADR 0011, and the judgement layer it turns into surface is AGENTS.md.

Install and configure

uv pip install digline-mcp

One server serves one repository: the perimeter is the repo, and multi-project is N named servers rather than a registry.

{
  "mcpServers": {
    "digline-northwind": {
      "command": "digline-mcp",
      "args": ["--root", "/Users/you/src/northwind"]
    }
  }
}

--tenant and --env are accepted and verify; they never override. The suite decides, as it does everywhere else in digline.

What run costs, before it costs it

run takes a mandatory acknowledge_calls that must equal the suite's planned calls to the target. Called without it, the tool refuses and hands back the number:

run(suite="suite.py")
  → refused: this suite plans 100 calls to the target.
    20 cases × 5 samples = 100 calls to the target; each answer is judged
    3 times by llm_rubric.
    Call again with acknowledge_calls=100.

run(suite="suite.py", acknowledge_calls=100)   → executes

The first call is the probe. An agent cannot spend a hundred model calls without having stated the number — AGENTS.md §7 as a contract rather than as advice.

What never crosses

An MCP response goes into a model's context, and from there into transcripts and caches nobody controls. So the run tools return a verdict-only projection: the name, the identity, the status, the score, the threshold, the tolerance, the measured interval, and the metadata a suite disclosed.

Never the judge's reason — the judge quotes the output, so the reason is the output. Never the sentence explaining a suspension, never undisclosed metadata, never a case's inputs, and never a prompt or its digest unless the suite declares Disclosure(artifacts=True).

Metadata

Release files for digline-mcp 0.4.6

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for digline-mcp 0.4.6
File Size Uploaded Provenance
digline_mcp-0.4.6.tar.gz 48.8 kB With provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for digline-mcp 0.4.6
File Interpreter ABI Platform
digline_mcp-0.4.6-py3-none-any.whl Python 3 none any Details

Total release size: 67.1 kB

Release files / digline_mcp-0.4.6.tar.gz

Download URL digline_mcp-0.4.6.tar.gz
Size 48.8 kB
Tags Source
SHA-256 checksum
How to use checksums
bf6f42aab79d41cf71b6684966b98e03d8a2821a307e521b9d91f9898e2a9c96
BLAKE2b-256 checksum
How to use checksums
7664c032c7ce714567eca7db6d342db3bc9921c861a0aa1738e38a5dfcc13efb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 7, 2026.

Transparency log

Release files / digline_mcp-0.4.6-py3-none-any.whl

Download URL digline_mcp-0.4.6-py3-none-any.whl
Size 18.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
cf0e2e8956409004223260dd9f4b8ac89042ccb4b9bb44ee8b71945aac101950
BLAKE2b-256 checksum
How to use checksums
66126306ef8094136afbcf9f82b387307f7f5a9ae38193da9a4a1b6a939610fd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 7, 2026.

Transparency log

Security for digline-mcp 0.4.6

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Full provenance

All 2 files in this release have been uploaded with provenance metadata.

Select from 2 files

Attestation for digline_mcp-0.4.6.tar.gz

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 7, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page