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one-context

Context compiler

Install / Use

claude mcp add m4vic -- npx -y github:m4vic/one-context

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

69/100

Supported Platforms

Claude Code
Claude Desktop

Tags

Our assessment of one-context

one-context scores 69/100 on our quality scale, 3868th of 4,610 Development & Engineering skills we index.

Its MCP Server is 5.3 KB long, well organised into 15 sections with 6 code examples: a solid amount of guidance for an agent.

It has 10 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
26/30
Structure
20/20
Description
4/15
Adoption
4/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated about 2 months ago, so one-context is actively maintained.
  • Our last check on 2026-09-29 found the source still online.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 87/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

one-context compared with similar skills

All 4 of these similar skills score higher than one-context; compare them before choosing.

SkillScoreStarsUpdatedFormat
one-context (this skill)by m4vic69102mo agoMCP Server
Agent-Reachby Panniantong100100.1ktodayCLAUDE.md
taste-skillby Leonxlnx10099.7ktodayCLAUDE.md
headroomby headroomlabs-ai10076.5ktodayCLAUDE.md
ai-job-searchby MadsLorentzen10059.2ktodayCLAUDE.md

Frequently asked questions

How do I install one-context?
Run claude mcp add m4vic -- npx -y github:m4vic/one-context. The install tabs above show the steps for each supported agent.
Which AI agents does one-context work with?
It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
Is one-context safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 87/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is one-context still maintained?
The repository was last updated about 2 months ago, so one-context is actively maintained.

[!WARNING]

Experimental Alpha

one-context is an experimental local context compiler. It is a research and learning project, not a production-ready context-management system.

The current v0.1.0-alpha.1 release explores automatic repository watching, deterministic project handoffs, optional LLM compression, and Claude/Codex integrations. These ideas are still being validated in real development workflows.

Do not rely on one-context for critical workflows, sensitive repositories, or irreplaceable engineering history without testing it independently first.

Development of the current compiler direction may pause or change while a more focused architecture-evolution skill is evaluated. There is no compatibility guarantee with the legacy MCP/Python implementation or future experiments.

Issues, feedback, and real-world failure reports are welcome.

<p align="center"> <img src="assets/1.png" alt="one-context logo" width="520"> </p>

one-context is a local background service that keeps project context compact and current. It is being shaped around a simple workflow:

  • auto-discover or register repos once
  • watch them in the background
  • compress meaningful changes into a small context artifact
  • let Claude, Codex, or another assistant read that artifact directly
<p align="center"> <img src="assets/screen.png" alt="one-context CLI" width="900"> </p>

Product direction

  • one command starts an onboarding flow, registers folders, starts the local background service, and writes assistant-ready artifacts automatically
  • the service compiles repository state from Git and file changes; it does not try to read a model's private conversation context
  • the default handoff is deterministic and always available
  • Ollama or an API can optionally improve the language of a handoff, but an LLM never becomes the source of truth

The current Go implementation is an early foundation. The intended v1 interface and delivery sequence are defined in IMPLEMENTATION_PLAN.md. Release evidence required before an alpha tag is listed in docs/RELEASE_GATE.md. Alpha installation and testing instructions are in docs/INSTALLATION.md.

Build

go build -o one-context.exe ./cmd/one-context

Current developer commands

.\one-context.exe --help
.\one-context.exe version
.\one-context.exe add F:\combinedcontext
.\one-context.exe status

# Machine-readable health for scripts.
.\one-context.exe status --json

add compiles the first handoff, starts the daemon when needed, and watches the repository automatically. File events are debounced; a 15-minute reconciliation scan catches events the operating system may have missed.

Check the generated artifacts without changing them:

.\one-context.exe validate

Enable automatic launch at login once, after installing the binary in a stable location:

.\one-context.exe startup install

In an interactive terminal, running one-context with no arguments opens the slash-command palette. Use /add and paste the folder to watch.

Assistant access

After registering a project, install each bridge once:

# Creates <project>/.claude/commands/one-context.md.
.\one-context.exe install claude F:\ASRT

# Creates the user-level Codex one-context skill.
.\one-context.exe install codex

# One command installs both bridges for this registered project.
.\one-context.exe install all F:\ASRT

Then, from F:\ASRT:

  • In Claude Code, enter /one-context.
  • In Codex, invoke $one-context in a new session if the skill was just installed.

Both bridges only read F:\ASRT\.one-context\context.md. They do not overwrite CLAUDE.md, AGENTS.md, or existing user instructions.

Compression today

Default mode is deterministic and does not need an LLM. It uses:

  • Git branch and recent commits
  • dirty working tree and bounded diff excerpts
  • active task and explicit handoff
  • standard repo anchor files such as README.md, AGENTS.md, and CLAUDE.md

When enabled, context.md remains the factual source of truth and llm-context.md becomes the separate model-written handoff. Configure it once:

# Local/private Ollama compression.
.\one-context.exe /llm ollama qwen3:4b

# OpenAI-compatible API compression. The key is never stored by one-context.
$env:ONE_CONTEXT_API_KEY = "..."
.\one-context.exe /llm api <model> [base-url]

# Anthropic Claude API.
$env:ANTHROPIC_API_KEY = "..."
.\one-context.exe /llm claude <model>

# Google Gemini API.
$env:GEMINI_API_KEY = "..."
.\one-context.exe /llm gemini <model>

# Limit provider attempts per UTC day. Use 0 for unlimited (the default).
.\one-context.exe /llm limit 25

# Keep global LLM settings but disable provider calls for one sensitive project.
.\one-context.exe config F:\ASRT --llm off

The provider and model are saved locally; API keys stay only in environment variables. Changing a provider refreshes enabled projects immediately. The daemon remains responsible for later automatic updates.

Remote providers receive a bounded handoff prompt containing selected Git and project evidence. one-context excludes common credential-file paths and redacts common token formats before the request, but this is defense in depth, not a guarantee that no sensitive data is sent. Use Ollama when source must remain on the machine.

Related Skills

View on GitHub
GitHub Stars10
CategoryDevelopment
Updated2mo ago
Forks0

Languages

Go

Trust signals

87/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

2 low1 info
one-context — MCP Server: Install & Safety Check | SkillAgent