Timepoint MCP

Timepoint MCP

Provides structured access to a temporal knowledge platform for searching historical events and browsing a causal graph of over 2,000 years of history. It enables users to generate rich historical scenes, interact with period-appropriate characters, and run complex temporal simulations.

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README

timepoint-mcp

MCP server for the Timepoint AI temporal knowledge platform.

Live at: mcp.timepointai.com

What is this?

A hosted Model Context Protocol server that gives AI agents structured access to the Timepoint ecosystem:

  • Search & browse a causal graph of 196+ historical moments spanning 2000+ years
  • Generate timepoints — rich historical scenes with narratives, characters, dialog, and AI images (coming soon)
  • Navigate time — step forward/backward from any moment to discover what came before and after (coming soon)
  • Chat with historical characters — in-context conversations with period-appropriate personalities (coming soon)
  • Run simulations — multi-entity temporal scenarios via the SNAG engine (coming soon)

Works with Claude Desktop, Cursor, Windsurf, VS Code Copilot, the Anthropic Agent SDK, and any MCP-compatible client.

Get an API key

Visit timepointai.com or reach out on X @timepointai to request access.

Clockchain read tools (search, browse, moment detail) work without authentication at 30 req/min. Generation and simulation tools require an API key and credits.

Quick start

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "timepoint": {
      "url": "https://mcp.timepointai.com/mcp",
      "headers": {
        "X-API-Key": "tp_mcp_..."
      }
    }
  }
}

Cursor / Windsurf

Add to .cursor/mcp.json or equivalent:

{
  "mcpServers": {
    "timepoint": {
      "url": "https://mcp.timepointai.com/mcp",
      "headers": {
        "X-API-Key": "tp_mcp_..."
      }
    }
  }
}

Anthropic Agent SDK

from claude_agent_sdk import Agent
from claude_agent_sdk.mcp import MCPServerRemote

agent = Agent(
    model="claude-sonnet-4-6",
    mcp_servers=[
        MCPServerRemote(
            url="https://mcp.timepointai.com/mcp",
            headers={"X-API-Key": "tp_mcp_..."},
        )
    ],
)
result = agent.run("What happened in Rome in 44 BC?")

Local development

git clone https://github.com/timepointai/timepoint-mcp.git
cd timepoint-mcp
pip install -e .

# stdio transport (for Claude Desktop local)
python -m app.server --transport stdio

# HTTP transport (for remote testing)
python -m app.server --transport http --port 8000

Available tools

Phase 1 (live now) — Clockchain read tools

Tool Auth Description
search_moments Optional Search the temporal causal graph for historical events
get_moment Optional Get full detail for a historical moment by its canonical path
browse_graph Optional Browse the graph hierarchy — year, month, day, location, event
get_connections Optional Get causal/thematic connections: what caused this, what it caused
today_in_history Key Events that happened on today's date across all eras
random_moment Key Random historical moment for serendipitous discovery
graph_stats Optional Node/edge counts, date range, source distribution

Phase 2 (coming soon) — Generation tools

Tool Credits Description
generate_timepoint 5-10 Generate a historical timepoint with scene, characters, dialog, image
temporal_navigate 2 Step forward/backward in time from an existing timepoint
chat_with_character 1 Converse with a historical character in context
get_timepoint 0 Retrieve a previously generated timepoint
list_my_timepoints 0 List your generated timepoints
get_credit_balance 0 Check credits and usage

Phase 3 (planned) — Simulation tools

Tool Credits Description
run_simulation 10 Run a SNAG temporal simulation
get_simulation_result 0 Get simulation results

Pricing

Tier Price Monthly Credits Rate Limit
Anonymous Free 30 req/min (read-only)
Free Free 5 signup credits 60 req/min
Explorer $7.99/mo 100 60 req/min
Creator $19.99/mo 300 300 req/min
Studio $49.99/mo 1,000 1,000 req/min

Credit packs also available as one-time purchases.

HTTP endpoints

In addition to the MCP protocol at /mcp, the server exposes:

Method Path Description
GET / Landing page (JSON for agents, redirect for browsers)
GET /health Service health check
GET /account/status Auth status and tier info
POST /admin/create-key Create API key (requires admin key)

Architecture

MCP Clients (Claude Desktop, Cursor, agents, SDKs)
        |
        | Streamable HTTP + X-API-Key
        v
   timepoint-mcp (mcp.timepointai.com)
   FastMCP + Starlette + asyncpg
        |
   -----+------+----------+
   |           |           |
   v           v           v
 Clockchain  Flash      Billing
 (graph)    (writer)   (Stripe/IAP)

The MCP server is a thin coordination layer. It authenticates requests via API keys, resolves user tiers via Billing, checks credit balance via Flash, routes tool calls to the appropriate backend, and enforces per-tier rate limits. It never stores credits or subscriptions — Flash and Billing own those.

Tech stack

  • Python 3.11+ with FastMCP, Starlette, httpx, asyncpg
  • Transport: Streamable HTTP (production), stdio (local dev)
  • Database: PostgreSQL (API keys + usage logs)
  • Deployment: Railway (Docker)

Environment variables

# Downstream services
FLASH_URL=https://api.timepointai.com
FLASH_SERVICE_KEY=...
FLASH_ADMIN_KEY=...
CLOCKCHAIN_URL=...
CLOCKCHAIN_SERVICE_KEY=...
BILLING_URL=...
BILLING_SERVICE_KEY=...

# Database
DATABASE_URL=postgresql://...

# Server
PORT=8000

License

Proprietary. Copyright 2026 Timepoint AI.

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