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lotus-wisdom-mcp

by linxule 36 stars linxule/lotus-wisdom-mcp

MCP server for structured problem-solving using the Lotus Sutra's wisdom framework. Beautiful visualizations, multiple thinking approaches, compatible with various MCP clients (e.g., Claude Desktop, Cursor, Cherry Studio).

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🪷 Lotus Wisdom MCP Server

Lotus Flower

An MCP server implementation that provides a tool for problem-solving using the Lotus Sutra's wisdom framework, combining analytical thinking with intuitive wisdom.

Available at: https://lotus-wisdom-mcp.linxule.workers.dev/mcp

Features

  • Multi-faceted problem-solving approach inspired by the Lotus Sutra
  • Step-by-step thought process with different thinking techniques
  • Meditation pauses to allow insights to emerge naturally
  • Interactive visualization via MCP ext-apps (Claude Desktop, Cursor, ChatGPT) — a pixel halo that lights one segment per step, in night and day variants that follow the host theme; keyboard-accessible and respects reduced motion
  • MCP Prompts (contemplate, deep-inquiry) for one-step guided contemplative sessions
  • Structured tool output (structuredContent + outputSchema) alongside the text response
  • Tracks both tag journey and wisdom domain movements
  • Available as a local stdio package (npx) or a hosted remote Connector
  • Final integration of insights into a clear response

Background

This MCP server was developed from the Lotus OS prompt, which was designed to implement a cognitive framework based on the Lotus Sutra. The MCP server format makes this framework more accessible and easier to use with Claude and other AI assistants.

The MCP server exposes the framework through tools and prompts. How well a model follows that framework depends on the model and host.

Implementation Details

The server implements a structured thinking process using wisdom domains inspired by the Lotus Sutra:

Wisdom Domains and Tags

The server organizes thoughts using wisdom domains (all valid values for the tag input parameter):

  • Entry (🚪): begin

    • Begin your journey here - receives the full framework before contemplation starts

  • Skillful Means (🔆): upaya, expedient, direct, gradual, sudden

    • Different approaches to truth - sometimes direct pointing, sometimes gradual unfolding

  • Non-Dual Recognition (☯️): recognize, transform, integrate, transcend, embody

    • Aspects of awakening to what's already present - recognition IS transformation

  • Meta-Cognitive (🧠): examine, reflect, verify, refine, complete

    • The mind watching its own understanding unfold

  • Process Flow (🌊): open, engage, express

    • A natural arc that can contain any of the above approaches

  • Meditation (🧘): meditate

    • Pausing to let insights emerge from stillness

Thought Visualization

In clients that support MCP ext-apps, each step renders inline as an interactive halo (see Interactive Visualization below). For every client, each step also returns:

  • Journey tracking showing both the tag path and the wisdom-domain movements
  • Domain-specific labels and the current contemplation text
  • Structured output (structuredContent + outputSchema) for programmatic consumers

Note: The local stdio server can emit per-step trace lines to its console (stderr) when run with LOTUS_DEBUG=true, helping developers follow the thinking process.

Process Flow

  1. The user submits a problem to solve
  2. The model begins with tag='begin' to receive the full framework
  3. The model continues with contemplation tags (open, examine, integrate, etc.)
  4. Each thought builds on previous ones and may revise understanding
  5. The tool tracks both the tag journey and wisdom domain movements
  6. Meditation pauses can be included for clarity
  7. When status='WISDOM_READY' is returned, the tool's work is complete
  8. The model then expresses the final wisdom naturally in its own voice

Available Tools

lotuswisdom

A tool for problem-solving using the Lotus Sutra's wisdom framework, with various approaches to understanding.

Begin your journey with tag='begin' - this returns the full framework (philosophy, domains, guidance) to ground your contemplation. Then continue with the other tags.

Inputs:

  • tag (string, required): The current processing technique (must be one of the tags listed above)
  • content (non-empty string, required): The content of the current processing step, including begin
  • stepNumber (integer, optional, default 1): Current number in sequence
  • totalSteps (integer, optional, default 5): Estimated total steps needed
  • nextStepNeeded (boolean, optional, default true): Whether another step is needed
  • isMeditation (boolean, optional): Whether this step is a meditative pause
  • meditationDuration (integer, optional): Duration for meditation in seconds (1-10)
  • previousJourney (string, optional): The journey string from a previous response, e.g. "begin → open → examine". Lets the AI carry journey continuity forward in stateless clients (such as the remote Worker), where the server keeps no session state.

Returns: a JSON text block and structuredContent validated against the tool's outputSchema. Every successful response includes journey for continuity, including begin and completion. Completion also retains finalJourney for compatibility. For begin, the full framework is in the text block; structured output contains its status, welcome, contemplation, journey, domain journey, and step counts. Other result variants retain their fields in both representations.

A meditation step with nextStepNeeded: false completes the inquiry with WISDOM_READY; ongoing meditation steps return MEDITATION_COMPLETE.

Response statuses include:

  • Processing status with current step information, wisdom domain, and journey tracking
  • FRAMEWORK_RECEIVED status on a begin step
  • MEDITATION_COMPLETE status for meditation steps
  • WISDOM_READY status when the contemplative process is complete

The tool declares readOnlyHint, idempotentHint, destructiveHint: false, and openWorldHint: false. These are host hints, not a guarantee of zero side effects: local stdio calls update the in-memory journey, and the hosted worker records usage analytics. The tools do not modify user files or external business data.

lotuswisdom_summary

Get a summary of the current contemplative journey.

Inputs:

  • previousJourney (string, optional): The journey string from a previous response, used to reconstruct the summary in stateless clients.

Returns:

  • Journey length
  • Domain journey showing movement between wisdom domains
  • Summary of all steps with their tags, domains, and brief content

MCP Prompts

The server registers two prompts that scaffold a guided contemplative session (surfaced as slash commands or prompt pickers in clients that support MCP Prompts):

  • contemplate — argument question: opens a single-question contemplation, instructing the model to start with tag='begin', iterate, and speak the wisdom only once status='WISDOM_READY'.
  • deep-inquiry — argument topic: begins a longer inquiry that moves deliberately across the wisdom domains (process → meta-cognitive → non-dual → meditation).

Usage

The Lotus Wisdom tool is designed for:

  • Breaking down complex problems requiring multi-faceted understanding
  • Questions that benefit from both direct and gradual approaches
  • Problems where apparent contradictions need integration
  • Situations requiring both analytical and intuitive understanding
  • Tasks that benefit from meditative pauses to allow insight
  • Questions containing their own inherent wisdom

Example Usage

Here's how a conversation with Claude might flow when using the Lotus Wisdom MCP server:

User: "Help me understand the relationship between freedom and responsibility."

Claude would begin the journey with tag='begin' to receive the framework, then continue:

  1. First, enter the contemplative space:
{
  "tag": "begin",
  "content": "Entering contemplation on freedom and responsibility.",
  "stepNumber": 1,
  "totalSteps": 6,
  "nextStepNeeded": true
}

→ Returns FRAMEWORK_RECEIVED with full framework

  1. Then, establish an opening thought:
{
  "tag": "open",
  "content": "The question explores the relationship between freedom and responsibility, which contain an apparent tension but also deep connection.",
  "stepNumber": 2,
  "totalSteps": 6,
  "nextStepNeeded": true
}
  1. Engage with different perspectives:
{
  "tag": "direct",
  "content": "Freedom and responsibility are two sides of the same coin. True freedom isn't absence of constraints but the capacity to choose our response within constraints.",
  "stepNumber": 3,
  "totalSteps": 6,
  "nextStepNeeded": true
}
  1. Perhaps take a meditation pause:
{
  "tag": "meditate",
  "content": "Contemplating how freedom without responsibility becomes chaos, and responsibility without freedom becomes oppression.",
  "stepNumber": 4,
  "totalSteps": 6,
  "nextStepNeeded": true,
  "isMeditation": true
}
  1. Integrate the understanding:
{
  "tag": "integrate",
  "content": "Freedom and responsibility mutually enable each other. Our freedom to choose gives rise to our responsibility for what we choose, and our willingness to take responsibility expands our freedom.",
  "stepNumber": 5,
  "totalSteps": 6,
  "nextStepNeeded": true
}
  1. Express the final understanding:
{
  "tag": "express",
  "content": "The paradox resolves when we see that authentic freedom includes responsibility as its natural expression.",
  "stepNumber": 6,
  "totalSteps": 6,
  "nextStepNeeded": false
}

When the tool returns status: 'WISDOM_READY', Claude then speaks the final wisdom naturally, integrating all the insights from the contemplative journey.

Installation

Install via Smithery for one-click setup, or follow the manual instructions below.

Requires Node.js 18+. The server runs locally via npx.

CLI Install (one-liner)

# Claude Code
claude mcp add lotus-wisdom -- npx -y lotus-wisdom-mcp

# Codex CLI (OpenAI)
codex mcp add lotus-wisdom -- npx -y lotus-wisdom-mcp

# Gemini CLI (Google)
gemini mcp add lotus-wisdom npx -y lotus-wisdom-mcp

Claude Desktop

Add to your claude_desktop_config.json:

OSConfig path
macOS~/Library/Application Support/Claude/claude_desktop_config.json
Windows%APPDATA%\Claude\claude_desktop_config.json
Linux~/.config/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "lotus-wisdom": {
      "command": "npx",
      "args": ["-y", "lotus-wisdom-mcp"]
    }
  }
}

VS Code

Add to .vscode/mcp.json (workspace) or open Command Palette > MCP: Open User Configuration (global):

{
  "servers": {
    "lotus-wisdom": {
      "command": "npx",
      "args": ["-y", "lotus-wisdom-mcp"]
    }
  }
}

Note: VS Code uses "servers" as the top-level key, not "mcpServers". Other VS Code forks (Trae, Void, PearAI, etc.) typically use this same format.

Cursor

Add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (project):

{
  "mcpServers": {
    "lotus-wisdom": {
      "command": "npx",
      "args": ["-y", "lotus-wisdom-mcp"]
    }
  }
}

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json (Windows: %USERPROFILE%\.codeium\windsurf\mcp_config.json):

{
  "mcpServers": {
    "lotus-wisdom": {
      "command": "npx",
      "args": ["-y", "lotus-wisdom-mcp"]
    }
  }
}

Cline

Open MCP Servers icon in Cline panel > Configure > Advanced MCP Settings, then add:

{
  "mcpServers": {
    "lotus-wisdom": {
      "command": "npx",
      "args": ["-y", "lotus-wisdom-mcp"]
    }
  }
}

Cherry Studio

In Settings > MCP Servers > Add Server, set Type to STDIO, Command to npx, Args to -y lotus-wisdom-mcp. Or paste in JSON/Code mode:

{
  "lotus-wisdom": {
    "name": "Lotus Wisdom",
    "command": "npx",
    "args": ["-y", "lotus-wisdom-mcp"],
    "isActive": true
  }
}

Witsy

In Settings > MCP Servers, add a new server with Type: stdio, Command: npx, Args: -y lotus-wisdom-mcp.

Codex CLI (TOML config)

Alternatively, edit ~/.codex/config.toml directly:

[mcp_servers.lotus-wisdom]
command = "npx"
args = ["-y", "lotus-wisdom-mcp"]

Gemini CLI (JSON config)

Alternatively, edit ~/.gemini/settings.json directly:

{
  "mcpServers": {
    "lotus-wisdom": {
      "command": "npx",
      "args": ["-y", "lotus-wisdom-mcp"]
    }
  }
}

Windows

On Windows, npx requires a shell wrapper. Replace "command": "npx" with:

{
  "command": "cmd",
  "args": ["/c", "npx", "-y", "lotus-wisdom-mcp"]
}

For CLI tools on Windows:

claude mcp add lotus-wisdom -- cmd /c npx -y lotus-wisdom-mcp
codex mcp add lotus-wisdom -- cmd /c npx -y lotus-wisdom-mcp

ChatGPT

ChatGPT only supports remote MCP servers over HTTPS. Use Smithery or connect directly to the hosted instance below via ChatGPT Settings > Connectors.

Remote (hosted)

A public instance is available at https://lotus-wisdom-mcp.linxule.workers.dev/mcp. No API key needed.

For clients supporting Streamable HTTP, connect directly to the URL. For stdio-only clients, use mcp-remote:

{
  "mcpServers": {
    "lotus-wisdom": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://lotus-wisdom-mcp.linxule.workers.dev/mcp"]
    }
  }
}

To self-host your own instance, see worker/README.md.

Building from source

Use Bun 1.4.2 and Node.js 24 to match CI.

bun install --frozen-lockfile
bun run typecheck
bun run test
bun run build
bun run test:package
bun run start

The build installs the app's locked dependencies and rebuilds the tracked dist/bundle.js and dist/journey.html artifacts. Check the app with cd app && bunx tsc --noEmit && bun run test. The suite covers the single-file build (the local Vite plugin inlines JavaScript and CSS into one HTML resource; tests cover dynamic imports and HTML escaping) and the journey itself: continuity across frames, meditation, reset between inquiries, exploration of the completed panel only, and every tag's character rendering from embedded outlines. See worker validation for the worker typecheck, dry-run build, and local HTTP regression.

To see a journey the way a chat shows it, one frame per call, run cd app && bunx vite build and open app/preview.html. The halo's characters are generated into app/src/glyphs.ts; app/scripts/glyphs.py regenerates them from a Noto Serif TC subset and documents how to fetch it.

bun run test:package packs the built files, installs the tarball in a temporary consumer directory, and starts npm's executable link. It checks the MCP version, tool discovery, a complete inquiry ending in meditation, a fresh inquiry reset, and the packaged journey HTML. CI runs this check after building and before publishing, so a broken launcher or missing package asset blocks the release. It requires npm registry access to install production dependencies and removes its temporary files on completion.

Dependabot uses the bun ecosystem for the root, app, and worker packages so updates include their bun.lock files. CI verifies all three packages on pull requests. Merging a PR updates source only: a version tag publishes to npm and the MCP Registry, and the Cloudflare Worker requires a separate deployment.

If npm publishes successfully but MCP Registry registration fails, retry only registration for the existing tag:

gh workflow run publish-mcp.yml --ref main -f registry_tag=vX.Y.Z

Replace vX.Y.Z with the existing published version's tag. This revalidates the tagged source and waits for npm availability before registration. It does not republish npm or move the release tag.

Enable debug mode:

LOTUS_DEBUG=true bun run start

Interactive Visualization (ext-apps)

In MCP clients that support ext-apps (Claude Desktop, Cursor, ChatGPT), each step renders inline as a small panel: a ring of pixels modeled on the LED halos (光背) wired behind temple statues, the step's character at its center, and the contemplation beside it. Each tool call gets its own panel, so a journey reads down the conversation one frame at a time.

  • The ring: one segment per step, shaded with the ASCII ramp: a ▒ track for steps still estimated to come, ▓ for earlier steps, solid █ for the current one, which dithers in as it arrives. The ring re-divides as totalSteps changes and closes exactly when the journey completes.
  • Color is attention: only the current step is in color; the rest is ink. The colors are the six of the Buddha's aura from the Buddhist flag: Entry white, Process red, Skillful Means yellow, Non-Dual orange, Meta-Cognitive blue, and Meditation the flag's sixth band, a pixel mosaic of all five. When the circle closes it turns white, every color at once (ink in daylight).
  • A character for each tag: every character comes from Kumārajīva's Lotus Sutra or from Tiantai's reading of it, in traditional forms. open, express, recognize and embody spell 開示悟入, the four aims of the Buddha's appearance in chapter 2, the chapter on skillful means, which also gives 巧 (upaya: 巧說諸法, "skillfully expounds the teachings") and 直 (direct: 正直捨方便, "directly setting means aside"). 照 (reflect) is the light across eighteen thousand worlds (ch. 1), 出 (transcend) the children leaving the burning house (ch. 3), 證 (verify) Many Treasures bearing witness (ch. 11), 淨 (refine) the purified senses (ch. 19). examine and meditate make Tiantai's 止觀. Hover a character for its pinyin and source. Characters are drawn from embedded Noto Serif TC outlines (SIL OFL 1.1), so they look the same with or without CJK fonts.
  • Meditation: the meditation segment breathes by pixel density three times, then rests.
  • Completion: the circle closes and turns white, segment by segment. Nothing is added underneath.
  • Look back: only the completed panel is interactive. Hover or focus a segment to see that step in its color with its character and tag; click or press Enter to pin it; arrow keys walk the ring. Panels for steps still in progress are for reading and do not respond to the pointer. Steps carried over from earlier frames show their place; their words stay in those frames.
  • Quiet by design: nothing loops, nothing glows, and with prefers-reduced-motion every state appears without animation. The design came out of a Lotus Wisdom journey on its own UI; after cd app && bunx vite build, open app/preview.html to replay that journey as a chat shows it, one frame per call.

Clients without ext-apps support are unaffected — they receive the same JSON tool responses as before.

How It Works

The Lotus Wisdom framework recognizes that wisdom often emerges not through linear thinking but through a dance between different modes of understanding. The tool facilitates this by:

  1. Tracking Wisdom Domains: As you move through different tags, the tool tracks which wisdom domains you're engaging, helping you see the shape of your inquiry.

  2. Journey Consciousness: The tool maintains awareness of your complete journey, showing both the sequence of tags used and the movement between wisdom domains.

  3. Non-Linear Progress: While steps are numbered, the process isn't strictly linear. You can revisit, revise, and branch as understanding deepens.

  4. Integration Points: Tags like integrate, transcend, and embody help weave insights together rather than keeping them separate.

  5. Natural Expression: The tool handles the contemplative process, but the final wisdom is always expressed naturally by the AI, not as formatted output.

Token Optimization Design

MCP tool descriptions stay in the AI's context window constantly when the server is connected. To minimize this overhead while preserving the full teaching content:

  • Constant context (~150 tokens): The lotuswisdom tool description is kept minimal—just enough for the AI to know when and how to use it
  • On-demand learning (~1,200 tokens): The complete framework is delivered when calling with tag='begin', including:
    • Philosophy and domain spirits
    • Parameter explanations (tag, content, stepNumber, etc.)
    • Response format details (wisdomDomain, journey, domainJourney)
    • Meditation handling (MEDITATION_COMPLETE status)
    • When to use guidance
  • Learn first, practice second: The begin tag ensures models receive complete understanding before contemplating

This approach reduces constant context overhead by ~85% when the tool is idle. When actually used, the full framework is delivered on first step—nothing is lost.

License

This MCP server is licensed under the MIT License. For more details, please see the LICENSE file in the project repository.

Contributing

Contributions are welcome! Please feel free to submit issues or pull requests on the GitHub repository.

Version

Current version: 0.9.0

What's New in 0.9.0

  • Redesigned the journey visualization as a pixel halo: one segment per step, a traditional character at its center, and the contemplation beside it. Earlier steps appear in ink, future steps as a dim track, and the current step in its domain color. The completed circle turns white in the night theme.
  • Added embedded Noto Serif TC glyph outlines, with pinyin and source notes on hover, so the characters render without installed CJK fonts or font requests.
  • Gave each event a finite animation and made only the completed panel explorable by hover, focus, pin, and keyboard navigation.
  • Kept completed panels at a steady height while looking back, with internal scrolling for longer earlier text, and fixed a rapid-hover content fade race.
  • Added a daylight palette that follows the host theme, reduced-motion styles, DOM regressions, and a development preview showing one frame per tool call.
  • Includes the journey reliability and dependency security fixes below; 0.8.6 was prepared but not published separately.

Reliability fixes prepared for 0.8.6 (included in 0.9.0)

  • Preserved the opening step in stateless journeys by returning continuity metadata from begin, including in structured output.
  • Fixed completion on meditation steps and added journey to completion responses while retaining finalJourney.
  • Reset the visualization between inquiries in reused iframes, including pending animations, collapsed steps, pins, and completion effects.
  • Added response-driven journey regressions for the installed CLI and worker, plus DOM tests for consecutive inquiries and animation races.
  • Updated dependencies and patched vulnerable transitive packages. The worker temporarily overrides Undici until Wrangler's Miniflare dependency is patched.

What's New in 0.8.1

  • Updated dependencies and GitHub Actions, regenerated Bun lockfiles, and added app and worker validation to CI.
  • Updated vulnerable transitive dependencies across all three packages and added dependency audits to CI. All three Bun audits passed during release validation on September 14, 2026.
  • Migrated the visualization to ext-apps 2 with its MCP client v2 and Zod 4 dependencies. The server transports remain on MCP SDK v1; the worker uses the agents SDK's explicit compatibility handler and retains stateless JSON responses.

What's New in 0.8.0

  • Single source of truth: domain logic, tool/server metadata, prompts, and the client parser now live in src/shared/ and are imported by both the stdio entry (index.ts) and the Cloudflare Worker — no more local-vs-remote drift
  • High-level McpServer everywhere: the local stdio server was migrated from the low-level Server API to McpServer, matching the Worker
  • MCP Prompts: contemplate and deep-inquiry for guided contemplative sessions
  • Structured tool output: tools now return structuredContent validated against an outputSchema, plus behavioral annotations (readOnlyHint, idempotentHint, destructiveHint: false, openWorldHint: false) and a server instructions field
  • Theme-aware, accessible UI: the ext-apps journey visualization adapts to the host light/dark theme and is keyboard-accessible
  • Security & cleanup: @modelcontextprotocol/sdk bumped to ^1.27.1, zod added, chalk removed; the legacy Express SSE server (server.ts), the express deps, and the Dockerfile were removed; the repo moved to bun lockfiles. Added a vitest test suite (tests/) and a single-source version workflow (src/shared/version.ts + bun run sync-version)
  • Server icon & website: server.json advertises the remote Worker (remotes[]), a websiteUrl, and icon sizes; the Worker advertises icons/website in the initialize handshake and serves the icon as same-origin bytes at /icon.png

What's New in 0.7.0

  • Fully stateless Worker: removed the Durable Object — the remote Worker now creates a fresh server per request and relies on the client-driven previousJourney parameter for journey continuity (eliminating accumulated SSE wall time)

What's New in 0.6.0

  • Server icon: added an icon to server.json and the Worker so MCP Registry and claude.ai Connectors display the lotus logo
  • Warmer UI and (since reverted) experimental Durable Object session state

What's New in 0.5.0

  • npm + MCP Registry publish: hardened packaging and published to npm and the official MCP Registry

What's New in 0.4.0

  • Interactive Visualization: MCP ext-apps UI renders a "Living Trace" journey inline in supporting clients (Claude Desktop, Cursor, ChatGPT)
  • Completion Fix: Any tag with nextStepNeeded=false now correctly returns WISDOM_READY (previously only express and complete could complete)
  • Cloudflare Worker: Worker deployment updated with ext-apps resource serving

What's New in 0.3.2

  • 🚪 Simplified Begin: tag='begin' can now be called with just {"tag":"begin"} - all other params auto-filled
  • 🤖 Better Haiku/Small Model Support: Removes friction for models that don't infer all required params

What's New in 0.3.1

  • 📚 Complete Framework Learning: begin tag now returns full parameter explanations, response format details, and meditation handling
  • 🔢 Accurate Token Counts: Updated documentation with actual token measurements (~150 constant, ~1,200 on-demand)

What's New in 0.3.0

  • 🚪 Begin Tag: New tag='begin' opens the journey—returns full framework before contemplation starts
  • ⚡ Optimized Token Footprint: Reduced constant context overhead from ~1400 to ~200 tokens while preserving full teaching content
  • 🧘 Learn First, Practice Second: The begin tag ensures models receive complete understanding before contemplating
  • 📦 Updated SDK: Upgraded to @modelcontextprotocol/sdk 1.23.0

What's New in 0.2.1

  • 📋 MCP Registry Enhancement: Added title field for better discoverability
  • 🎯 Full Compliance: Now fully compliant with official MCP publishing guide
  • 🔗 Registry Links: Available on Official MCP Registry

What's New in 0.2.0

  • 🌐 HTTP Transport Support: Now deployable on smithery.ai and other HTTP-based platforms
  • 🔄 Dual Transport: Maintains stdio support for npm/CLI users while adding HTTP for remote deployment
  • 📦 Updated SDK: Upgraded to @modelcontextprotocol/sdk 1.20.1 with Streamable HTTP support
  • 🪷 New Logo: Terminal-aesthetic lotus logo perfect for developer tools
  • ⚡ Session Management: HTTP version includes full session management for stateful wisdom journeys

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