ArchLog MCP
Provides Git-based version control integration, enabling comparison of two Git references (commits, tags, branches) to generate traceable release notes.
Allows analysis of public GitHub C/C++ repositories for architecture-guided release-note generation, cloning repositories and retrieving code changes between Git references.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ArchLog MCP start analysis for https://github.com/curl/curl from curl-7_80_0 to curl-7_81_0"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ArchLog MCP
ArchLog MCP is a Windows-first local STDIO MCP server for architecture-guided software release-note generation. A user supplies a public GitHub C/C++ repository and two Git references; an agent can start the analysis, monitor the persistent job, and return the generated traceable release-note path.
This repository is a self-contained source distribution. It includes the pinned
ArchLog runtime snapshot, ENRE-CPP JAR, and the SemArc-RAG runtime source under
runtime/archlog. It does not depend on a sibling ArchLog checkout or a
prebuilt SemArcArcRN.exe directory.
Current support
Windows x64
Python 3.12 x64
Java 17 or newer and Git on
PATHPublic HTTPS GitHub repositories
C and C++ repositories
Chinese release-note output
SiliconFlow model
deepseek-ai/DeepSeek-V4-FlashSILICONFLOW_API_KEYfrom the user's environmentOptional but strongly recommended
GITHUB_TOKEN
SemArc runs from the committed SemArc_RAG/run_for_arcrn.py source entrypoint
and uses its own depends dependency backend. ENRE-CPP remains independent
ArchLog change evidence.
Related MCP server: DevForge-MCP
Install from source
Clone this repository, then run the supported installer from PowerShell:
git clone https://github.com/<owner>/ArchLog-MCP.git
cd ArchLog-MCP
powershell -NoProfile -ExecutionPolicy Bypass -File .\scripts\install-from-source.ps1The installer is idempotent. It creates .venv, installs the fully resolved
runtime versions from requirements/source-runtime.lock.txt, installs required
NLTK data, and performs an MCP environment check. It never asks for, writes, or
prints API keys. Dependency downloads can take several minutes.
Set secrets in the user environment before launching the agent, then restart the agent so it inherits them:
[Environment]::SetEnvironmentVariable("SILICONFLOW_API_KEY", "<key>", "User")
[Environment]::SetEnvironmentVariable("GITHUB_TOKEN", "<token>", "User")Register in Qoder
With Qoder CLI installed, register ArchLog for the current user:
powershell -NoProfile -ExecutionPolicy Bypass -File .\scripts\register-qoder.ps1 -Scope userStart a new Qoder Agent session or run /mcp reload, then ask Qoder to call
archlog_check_environment. The template under adapters/qoder can be used in
Qoder Settings > MCP when Qoder CLI is unavailable.
Let an agent install it
The following instruction is suitable for Qoder or another coding agent with a terminal. Replace the repository URL first:
Clone the ArchLog-MCP repository from
<repository-url>. Read its README, run onlyscripts/install-from-source.ps1, preserve my existing environment variables, register the installed launcher as a user-level STDIO MCP, and runarchlog_check_environment. Ask before downloading dependencies or changing agent configuration. Do not read, print, or store API-key values, and do not start an analysis yet.
Installation cannot be completely silent: the user should approve dependency downloads and the MCP configuration change.
MCP job contract
The server exposes:
archlog_check_environmentarchlog_validate_requestarchlog_start_analysisarchlog_get_statusarchlog_get_resultarchlog_get_failure_reportarchlog_resume_analysisarchlog_cleanup_intermediate_results
Call archlog_start_analysis once with an idempotency key and poll no more often
than next_poll_after_seconds. Only state=succeeded with a validated result is
success. Process exit, directory presence, and partial stage output are not
success indicators.
On Windows, the server first launches a worker with
CREATE_BREAKAWAY_FROM_JOB. If an agent host such as Qoder forbids that flag,
ArchLog MCP uses a transient per-job Windows Task Scheduler task instead. This
keeps a long analysis alive after the short STDIO MCP request returns. The
fallback writes only non-secret runtime paths to the job directory; API keys and
GitHub tokens are never placed in task arguments or worker setting files. The
worker removes its transient task registration when it reaches a terminal
result. The current Windows user must be allowed to register limited,
interactive scheduled tasks.
Confirmed cleanup permanently removes repositories, logs, external-analysis
output, and intermediate pipeline artifacts. It retains
final_release_note_traceable.md, manifest.json, request.json, and the job
database record.
Repository layout
src/archlog_mcp: STDIO server, persistence, validation, and job managementruntime/archlog: committed analysis runtime snapshotruntime/archlog/third_party_tools/ENRE-CPP.jar: ENRE-CPP runtimeruntime/archlog/third_party_tools/SemArc_RAG: headless SemArc source runtimerequirements/source-runtime.lock.txt: pinned source-install dependenciesscripts/install-from-source.ps1: supported source installerscripts/verify-install.ps1: MCP handshake and environment verificationscripts/register-qoder.ps1: Qoder user/local/project registrationscripts/sync_source_runtime.py: maintainer-only runtime snapshot generatorscripts/runtime_overrides: lightweight compatibility files applied during runtime syncadapters: client configuration examples
SOURCE_RUNTIME_MANIFEST.json records the ArchLog source commit and SHA-256 of
every committed runtime file. Maintainers regenerate the snapshot explicitly;
end users do not need a second repository.
Mutable data and safety
The installation tree is treated as immutable during analysis. Jobs, cloned
repositories, logs, checkpoints, and final release notes are stored under
%LOCALAPPDATA%\ArchLog-MCP unless ARCHLOG_MCP_DATA_ROOT is set.
The controlled mock engine is available only through the explicit development
setting ARCHLOG_MCP_ENGINE_MODE=mock. Production mode is the default.
Maintainer runtime refresh
After reviewing an authoritative ArchLog checkout, regenerate the committed runtime snapshot with:
python .\scripts\sync_source_runtime.py --archlog-root C:\path\to\ArchLogReview the manifest and run the full test and isolated-install suite before
committing the refresh. Do not commit .venv, caches, jobs, logs, experiment
outputs, or the PyInstaller SemArc distribution.
Available Tools
3 toolsarchlog_check_environmentA
Check the local ArchLog, ENRE-CPP, SemArc, Git, Java, data path, and LLM configuration without starting an analysis.
Inputs: no named parameters. Returns: object
archlog_start_analysisA
Start an asynchronous architecture-guided release-note analysis and return immediately with a persistent job ID. Poll with archlog_get_status; do not wait in this call.
Inputs: base_ref (required), head_ref (required), repo_url (required), idempotency_key, +1 more. Returns: object
archlog_validate_requestA
Validate and normalize a GitHub C/C++ release range. This performs no checkout and starts no analysis.
Inputs: base_ref (required), head_ref (required), repo_url (required), output_language. Returns: object
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: starting an analysis, checking the environment, and validating a request. There is no overlap or ambiguity.
All tool names follow a consistent 'archlog_verb_noun' pattern, making them predictable and easy to understand.
Three tools are appropriate for the server's focused scope of architecture-guided release-note analysis, covering essential steps without being excessive or thin.
The set references a 'archlog_get_status' tool for polling, but it is missing from the provided tools. This is a significant gap that would cause agent failures when trying to retrieve analysis results.
Maintenance
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