@ai-dossier/mcp-server

@ai-dossier/mcp-server

MCP server that lets any MCP-capable LLM discover, verify, and run dossiers — portable, signed skills — through the Model Context Protocol. If you've used Claude Code skills, dossiers will feel familiar: they're skills you can verify, version, and pull from a registry.

Installation

Claude Code Plugin (Recommended)

/plugin marketplace add imboard-ai/ai-dossier
/plugin install dossier-mcp-server@ai-dossier

One-time setup — auto-updates included.

Claude Code (Manual)

# Global (available across all projects)
claude mcp add dossier --scope user -- npx @ai-dossier/mcp-server

# Project-only
claude mcp add dossier -- npx @ai-dossier/mcp-server

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "dossier": {
      "command": "npx",
      "args": ["-y", "@ai-dossier/mcp-server"]
    }
  }
}

Verify

claude mcp list

Then try:

"List available dossiers in this project"
"Execute the project-init dossier"

Tools

Discovery & Reading

Tool	Description
list_dossiers	Discover available dossiers in a directory. Scans for *.ds.md files and returns metadata.
read_dossier	Read and parse a dossier file. Returns metadata and content. Should be called after verify_dossier passes.
search_dossiers	Search the dossier registry for available dossiers by keyword and optional category filter.

Security Verification

Tool	Description
verify_dossier	Verify integrity (checksum) and authenticity (signature) of a single dossier. Returns pass/fail with stage details.
verify_graph	Batch verify all dossiers in a resolved dependency graph. Returns aggregate security report with per-dossier breakdown.

Orchestration (Multi-Dossier Journeys)

Tool	Description
resolve_graph	Resolve a dossier dependency graph into an execution plan. Produces a DAG with ordered phases, parallel groups, and conflict detection.
start_journey	Start a journey session from a resolved and verified graph. Returns the first step's dossier content with injected context.
step_complete	Mark the current journey step as complete or failed. Advances to the next step with context from previous outputs.
get_journey_status	Get the current state of a journey: completed steps, current step, remaining steps, and collected outputs.
cancel_journey	Cancel an active journey session. Returns a summary of what completed before cancellation.

Resources

URI	Description
dossier://concept	Introduction to dossiers — what they are and why to use them
dossier://protocol	How to execute dossiers safely and effectively
dossier://security	Security model, signing, verification, and trust management
dossier://orchestration	Complete reference for multi-dossier journey tools

Prompts

Prompt	Description
execute-dossier	Run a dossier with verification and protocol. Automatically chooses single or multi-dossier flow based on relationships.
execute-journey	Guide through a multi-step dossier journey: resolve, verify, present plan, execute steps, collect outputs.
create-dossier	Author a new dossier using the official meta-dossier template.

Security

Every dossier execution is verified before running:

User: "Execute the deploy-to-aws dossier"

LLM:  *Calls verify_dossier*

      Security Verification:
      - Integrity: Checksum verified (content not tampered with)
      - Authenticity: Signed by imboard-ai-2024 (trusted)
      - Risk Level: HIGH

      This dossier will modify AWS infrastructure.
      Proceed? (y/N)

Verification results

• ALLOW — Verified signature from trusted source + low risk. Execute confidently.
• WARN — Unsigned/unknown signer or high risk. Request user approval.
• BLOCK — Checksum failed or signature invalid. Do not execute.

Features

• Integrity: SHA256 checksums ensure dossiers haven't been modified
• Signatures: Optional minisign cryptographic signatures
• Risk assessment: Declared risk level and specific risk factors per dossier
• Trust model: Decentralized — users choose which signing keys to trust via ~/.dossier/trusted-keys.txt

Development

git clone https://github.com/imboard-ai/ai-dossier.git
cd ai-dossier/mcp-server
npm install
npm run build
npm test
npm start

Project structure

mcp-server/
  src/
    index.ts                 # Server entry point
    tools/                   # Tool implementations
    resources/               # Resource providers
    orchestration/           # Graph resolution, sessions, output mapping
    utils/                   # Logger, CLI wrapper, response helpers

Technical Details

• Protocol: MCP (Model Context Protocol)
• Language: TypeScript
• Runtime: Node.js 20+
• Transport: stdio
• Dependencies: @modelcontextprotocol/sdk, @ai-dossier/core
• License: AGPL-3.0

For AI Agents

npm run build -w mcp-server    # build (requires core built first)
npm run test -w mcp-server     # test
make build-mcp                 # build core + mcp-server together

• src/index.ts — server entry: registers all tools, resources, and prompts
• src/tools/ — one file per MCP tool (e.g. verifyDossier.ts)
• src/resources/ — static MCP resources (concept, protocol, security, orchestration)
• src/orchestration/ — graph resolution and journey session management
• src/utils/ — logger, CLI wrapper, response helpers

Adding a tool: create src/tools/myTool.ts, export handler + input type, register in src/index.ts (add to ListTools + CallTool switch).

Adding a resource: create src/resources/myResource.ts, register in src/index.ts (add to ListResources + ReadResource switch).

For dossier users (not contributors): install via claude mcp add dossier -- npx @ai-dossier/mcp-server to get dossier:// resources and tools at runtime. MCP Registry name: ai.imboard/dossier.

Links

• Specification
• Changelog
• Dossier Standard
• Examples