MCP server for Hoshin Kanri: a living X-Matrix your AI agent can read, challenge and update. 11 tools, 9 prompts, 3 transports — including a sovereign local JSON mode where your strategy never leaves your machine.
git clone https://github.com/wellknownmcp/hoshin-kanri{
"mcpServers": {
"hoshin-kanri": {
"command": "node",
"args": ["/path/to/hoshin-kanri/dist/index.js"]
}
}
}MCP Servers overview
# Hoshin Kanri — MCP server
The MCP server behind [hoshin.app](https://hoshin.app): a living **X-Matrix**
your AI agent can read, challenge and update — 3-to-5-year objectives, annual
objectives, initiatives, KPIs, the correlations between them, the review
cadences that keep them alive, and a completeness score that gives a verdict
instead of a vibe.
**11 tools · 9 guided prompts · 3 transports · MIT.**
Registry entry: [`io.github.wellknownmcp/hoshin-kanri`](https://registry.modelcontextprotocol.io)
· npm: [`hoshin-kanri-mcp`](https://www.npmjs.com/package/hoshin-kanri-mcp)
## Why this exists
Agents are good at doing the work and bad at knowing which work matters. The
missing piece is not more memory — it is *structured* strategic memory: an
object with quadrants, correlations and a score, so an agent can answer "does
this initiative actually serve a stated objective?" and be wrong out loud when
it does not.
That object is the X-Matrix, a Hoshin Kanri artifact that predates all of this
by forty years. This server exposes it over the Model Context Protocol.
## Install
### Sovereign local mode — nothing leaves your machine
Your matrix lives in plain JSON files on your own disk. No account, no cloud,
no telemetry. This is the default binary of the npm package, on purpose.
```json
{
"mcpServers": {
"hoshin-kanri": {
"command": "npx",
"args": ["-y", "hoshin-kanri-mcp"],
"env": { "HOSHIN_DATA_DIR": "/path/to/your/data" }
}
}
}
```
`HOSHIN_DATA_DIR` defaults to `~/hoshin-data/`. The files *are* the export:
readable, diffable, versionable, yours. See [docs/data-residency.md](docs/data-residency.md).
### Hosted mode — OAuth 2.1, nothing to install
claude.ai, Claude Desktop and Cursor connect straight to `https://hoshin.app/mcp`.
Dynamic client registration + PKCE, so there is no token to paste and no
config file to edit — add the URL as a connector and authorize.
<details>
<summary>Or with a static API token, over stdio</summary>
```json
{
"mcpServers": {
"hoshin-kanri": {
"command": "npx",
"args": ["-y", "-p", "hoshin-kanri-mcp", "hoshin-kanri-mcp-remote"],
"env": { "AUTH_TOKEN": "hk_..." }
}
}
}
```
</details>
## What is in here
| Path | What |
|---|---|
| `mcp-server/index-local.js` | stdio transport, local JSON store — the npm default bin |
| `mcp-server/index-stdio.js` | stdio transport against the hosted API |
| `mcp-server/index-streamable-http.js` | Streamable HTTP transport, the one serving `hoshin.app/mcp` |
| `mcp-server/lib/tool-definitions.js` | the 11 tool schemas, shared by all three transports |
| `mcp-server/lib/prompt-definitions.js` | the 9 guided prompts, shared by all three transports |
| `mcp-server/lib/completeness.js` | the completeness score, as pure functions |
| `mcp-server/lib/json-store.js` | atomic local JSON store (tmp + rename, in-process mutex) |
| `docs/completeness-score.md` | the score specification — metrics, weights, response shape |
| `docs/data-residency.md` | where your strategy lives, per transport |
| `server.json` | the MCP registry manifest |
Tool and prompt *definitions* are shared across transports by design: only the
handlers differ. A tool that exists in hosted mode and not in local mode would
quietly make the sovereign mode a second-class citizen, so parity is a rule,
not an aspiration — with one deliberate exception, documented below.
## Tools
`get_matrix_data` · `get_matrix_summary` · `get_matrix_completeness` ·
`list_objectives` · `update_element_status` · `add_idea` · `search_ideas` ·
`get_management_architecture` · `diagnose_theme_deployment` ·
`suggest_meeting_for_topic` · `share_matrix`
Two worth calling out:
- **`get_matrix_completeness`** returns a 0–100 score across five metrics
(coverage, correlation density, orphan elements, end-to-end strategic chains,
leading/lagging indicator balance) with the specific suggestions behind it.
This is the part that makes an agent useful rather than agreeable.
- **`update_element_status`** accepts an `external_ref` — the URL or key of the
Linear/Jira/GitHub project implementing that initiative. Strategy lives here,
tasks live in your execution tool, and the `weekly_sync` prompt walks an agent
across both.
`share_matrix` publishes a revocable, read-only public page of a matrix. It is
**refused in local mode** — by design: in sovereign mode there is no cloud for
your data to leak into, so there is nothing to publish from.
## Prompts
`weekly_sync` (pull execution progress from your issue tracker's MCP, update
statuses, prepare the weekly agenda) · `matrix_artifact` (a boardroom-ready
interactive X-Matrix) · `strategic_review` · `deployment_diagnosis` ·
`indicator_balance` · `meeting_setup_guide` · `visual_matrix` · `export_data` ·
`idea_triage`
## Development
```bash
cd mcp-server
pnpm install
pnpm start:local # sovereign JSON mode
pnpm start:stdio # hosted API mode (AUTH_TOKEN, API_BASE_URL)
pnpm start # Streamable HTTP (server-side; MCP_PORT, API_BASE_URL, OAUTH_ISSUER)
```
Smoke-test the local transport without any client:
```bash
printf '%s\n' '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-06-18","capabilities":{},"clientInfo":{"name":"smoke","version":"1"}}}' \
| HOSHIN_DATA_DIR=/tmp/hoshin-smoke node index-local.js 2>/dev/null
```
stdout carries JSON-RPC only; logs and the startup banner go to stderr.
This repository holds the MCP server and its specifications. The hosted web
application (Next.js, Prisma, the OAuth 2.1 authorization server) is a separate,
closed codebase — the MIT code here is what you run, and what you can audit
before running it.
Issues and pull requests are welcome, in English or French.
## Learn more
- [What is Hoshin Kanri?](https://hoshin.app/what-is-hoshin-kanri)
- [AI in lean management: start with steering](https://hoshin.app/ai-lean-management)
- [Model Context Protocol](https://modelcontextprotocol.io)
MIT — the code is a commodity; your strategy is not.
What people ask about hoshin-kanri
What is wellknownmcp/hoshin-kanri?
+
wellknownmcp/hoshin-kanri is mcp servers for the Claude AI ecosystem. MCP server for Hoshin Kanri: a living X-Matrix your AI agent can read, challenge and update. 11 tools, 9 prompts, 3 transports — including a sovereign local JSON mode where your strategy never leaves your machine. It has 0 GitHub stars and was last updated today.
How do I install hoshin-kanri?
+
You can install hoshin-kanri by cloning the repository (https://github.com/wellknownmcp/hoshin-kanri) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is wellknownmcp/hoshin-kanri safe to use?
+
wellknownmcp/hoshin-kanri has not been audited yet by our security agent. Review the original repository on GitHub before using it in production.
Who maintains wellknownmcp/hoshin-kanri?
+
wellknownmcp/hoshin-kanri is maintained by wellknownmcp. The last recorded GitHub activity is from today, with 0 open issues.
Are there alternatives to hoshin-kanri?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
Deploy hoshin-kanri to your cloud
Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.
Maintain this repo? Add a badge to your README
Drop the badge into your GitHub README to show it's tracked on ClaudeWave. Each badge links back to this page and reflects the live Trust Score.
[](https://claudewave.com/repo/wellknownmcp-hoshin-kanri)<a href="https://claudewave.com/repo/wellknownmcp-hoshin-kanri"><img src="https://claudewave.com/api/badge/wellknownmcp-hoshin-kanri" alt="Featured on ClaudeWave: wellknownmcp/hoshin-kanri" width="320" height="64" /></a>More MCP Servers
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
An open-source AI agent that brings the power of Gemini directly into your terminal.
The fastest path to AI-powered full stack observability, even for lean teams.
Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface
🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!