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mcp-server

Model Context Protocol server for AI integration with Echoes storytelling platform

Installation

The server is distributed as an npm package and can be used without cloning the repository.

Using with MCP Clients

The server can run in three modes depending on the working directory:

Single Timeline Mode: Run from a timeline-* directory to work with that specific timeline
Multi-Timeline Mode: Run from .github directory to access all timelines
Test Mode: Run from mcp-server directory for development

Single Timeline Configuration (Recommended for Kiro CLI)

{
  "mcpServers": {
    "echoes": {
      "command": "npx",
      "args": ["-y", "@echoes-io/mcp-server"],
      "cwd": "/path/to/timeline-pulse"
    }
  }
}

Multi-Timeline Configuration (Legacy/CAO)

{
  "mcpServers": {
    "echoes": {
      "command": "npx",
      "args": ["-y", "@echoes-io/mcp-server"],
      "cwd": "/path/to/echoes-io/.github"
    }
  }
}

Or install globally:

npm install -g @echoes-io/mcp-server

Then configure:

{
  "mcpServers": {
    "echoes": {
      "command": "echoes-mcp-server",
      "cwd": "/path/to/timeline-pulse",
      "env": {
        "ECHOES_RAG_PROVIDER": "qwen3"
      }
    }
  }
}

Optional RAG Configuration:

ECHOES_RAG_PROVIDER: Embedding provider (qwen3, nomic-embed, bge-base, e5-large, e5-small, or gemini). Default: qwen3
ECHOES_GEMINI_API_KEY: Required if using gemini provider

Execution Modes

Single Timeline Mode (Recommended)

Run from a timeline directory to work with that specific timeline:

cd timeline-pulse
npx @echoes-io/mcp-server
# [DEBUG] Mode: single-timeline "pulse"

Benefits:

Simpler configuration for single-timeline workflows
Direct access to timeline databases
Perfect for Kiro CLI integration

Multi-Timeline Mode (Legacy)

Run from .github directory to access all timelines:

cd .github
npx @echoes-io/mcp-server
# [DEBUG] Mode: multi-timeline (scanning /path/to/echoes-io)

Benefits:

Manage multiple timelines simultaneously
Backward compatible with CAO agents
Timeline repositories can be private

Test Mode

Run from mcp-server directory for development:

cd mcp-server
npm run dev
# [DEBUG] Mode: test from mcp-server (in-memory)

Timeline Architecture

Each timeline has isolated databases in its own repository:

echoes-io/
  .github/              # Multi-timeline mode runs from here
  timeline-eros/        # Private timeline repo
    tracker.db          # Timeline-specific database
    lancedb/            # Timeline-specific RAG vector database
    content/...
  timeline-other/       # Another private timeline
    tracker.db
    lancedb/
    content/...

Benefits:

Each timeline has isolated databases in its own repository
Timeline repositories can be private while .github is public
No need to specify contentPath - auto-discovered from directory structure
Easy to manage access: just share/don't share specific timeline repos

Available Tools

All tools require a timeline parameter to specify which timeline to operate on.

Content Operations

words-count - Count words and text statistics in markdown files
- Input: file (path to markdown file)
chapter-info - Extract chapter metadata from database
- Input: arc, episode, chapter
chapter-refresh - Refresh chapter metadata and word counts from file
- Input: file (path to chapter file)
chapter-insert - Insert new chapter with automatic renumbering
- Input: arc, episode, after, pov, title, optional: summary, location, outfit, kink, file
chapter-delete - Delete chapter from database and optionally from filesystem
- Input: arc, episode, chapter, optional: file (to delete from filesystem)

Episode Operations

episode-info - Get episode information and list of chapters
- Input: arc, episode
episode-update - Update episode metadata (description, title, slug)
- Input: arc, episode, optional: description, title, slug

Timeline Operations

timeline-sync - Synchronize filesystem content with database
- Input: timeline (timeline name)
- Note: Content path is auto-discovered from timeline directory structure

Statistics

stats - Get aggregate statistics with optional filters
- Input: timeline, optional: arc, episode, pov
- Output: Total words/chapters, POV distribution, arc/episode breakdown, longest/shortest chapters
- Examples:
  - No filters: Overall timeline statistics
  - arc: "arc1": Statistics for specific arc
  - arc: "arc1", episode: 1: Statistics for specific episode
  - pov: "Alice": Statistics for specific POV across timeline

RAG (Semantic Search)

rag-index - Index chapters into vector database for semantic search
- Input: timeline, optional: arc, episode (to index specific content)
- Output: Number of chapters indexed
- Note: Content path is auto-discovered from timeline directory structure
- Note: Automatically extracts character names using NER (Named Entity Recognition)
rag-search - Semantic search across timeline content
- Input: timeline, query, optional: arc, pov, maxResults, characters, allCharacters
- Output: Relevant chapters with similarity scores, previews, and character names
- Character filtering:
  - characters: Array of character names to filter by
  - allCharacters: If true, all characters must be present (AND). If false, at least one (OR). Default: false
- Examples:
  - characters: ["Alice", "Bob"], allCharacters: true - Find chapters where both Alice AND Bob appear
  - characters: ["Alice", "Bob"] - Find chapters where Alice OR Bob appear
rag-context - Retrieve relevant context for AI interactions
- Input: timeline, query, optional: arc, pov, maxChapters, characters
- Output: Full chapter content for AI context with character names
- Supports character filtering like rag-search
rag-characters - Get all characters that appear in chapters with a specific character
- Input: timeline, character (character name)
- Output: List of co-occurring characters sorted alphabetically
- Use case: "Who does character X interact with?"

Book Generation

book-generate - Generate PDF book from timeline content using LaTeX
- Input: timeline, outputPath, optional: episodes, format
- Output: PDF book with Victoria Regia template
- Formats: a4 (default), a5
- Requirements: pandoc, LaTeX distribution (pdflatex/xelatex/lualatex)
- Note: Content path is auto-discovered from timeline directory structure

Development

Scripts

# Run tests
npm test

# Run tests with coverage
npm run test:coverage

# Build
npm run build

# Lint
npm run lint

# Fix linting issues
npm run lint:format

Tech Stack

Language: TypeScript (strict mode)
Testing: Vitest (90.71% coverage, 82 tests)
Linting: Biome (0 warnings)
Build: TypeScript compiler

Architecture

MCP Protocol: Standard Model Context Protocol implementation
Database: SQLite via @echoes-io/tracker (singleton pattern)
Validation: Zod schemas for type-safe inputs
Testing: Comprehensive unit and integration tests
Timeline Parameter: All tools accept timeline as a required parameter

License

MIT

Part of the Echoes project - a multi-POV digital storytelling platform.