Read-only global event and evidence intelligence with entities, assets, and impact paths.
Open-source developer tools for The Neural Ledger intelligence API.
TNL Intelligence gives AI agents and quantitative research systems structured, source-linked global event intelligence. It is an evidence and research layer, not a broker, an order router, or a source of trading-grade prices.
| Package | Purpose |
|---|---|
@theneuralledger/sdk | Typed TypeScript client for the TNL /v1 API |
@theneuralledger/mcp | Read-only MCP server over stdio or Streamable HTTP |
@theneuralledger/gateway | Hosted OAuth, tenant policy, quota, and audit MCP gateway |
@theneuralledger/onboarding | Developer credentials, static sample API, and explorer |
@theneuralledger/events | Webhook contracts, signed delivery, and verification helpers |
@theneuralledger/research | Evidence-first skills, orchestration, MCP App, and web UI |
@theneuralledger/adapters | Shared Cursor and OpenAI workflow contracts and rendering |
@theneuralledger/connectors | Shared n8n, Pipedream, and Zapier action/trigger contracts |
@theneuralledger/cli | tnl CLI, watch command, local cache, and foreground daemon |
tnl-intelligence | Python SDK and optional point-in-time quant research toolkit |
Set a member API key in the environment:
export TNL_API_KEY="..."
Run the MCP server over stdio:
npx -y @theneuralledger/mcp
Or run its localhost Streamable HTTP endpoint:
docker compose up --build
curl http://127.0.0.1:7317/healthz
Use the CLI:
npx -y @theneuralledger/cli latest
npx -y @theneuralledger/cli search "Federal Reserve"
Use the TypeScript SDK:
import { TnlClient } from '@theneuralledger/sdk';
const client = new TnlClient({ apiKey: process.env.TNL_API_KEY! });
const page = await client.listNews({ sort: 'pipeline', pageSize: 20 });
Use the Python SDK:
from tnl_intelligence import TnlClient
with TnlClient(api_key="...") as client:
page = client.list_news(sort="pipeline", page_size=20)
127.0.0.1 by default.See SECURITY.md and the build plan. Research deployment boundaries and staged rollout are documented in Research operations.
npm install
npm run openapi:sync
npm run validate
Python development uses the project under python/tnl_intelligence.
MIT
Source-derived launch command. Check the maintainer’s required arguments and credentials before running:
npx -y @theneuralledger/mcpMerge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.
{
"mcpServers": {
"com-theneuralledger-intelligence": {
"command": "npx",
"args": [
"-y",
"@theneuralledger/mcp"
]
}
}
}Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.
Claude Desktop setup referenceThe Neural Ledger Intelligence works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.