NodeBench AI

Entity intelligence for any company, market, or question.

Live: nodebenchai.com
npm: npx nodebench-mcp / npx nodebench-mcp-power / npx nodebench-mcp-admin
GitHub: HomenShum/nodebench-ai

Product

NodeBench is a research and reporting product built around five user-facing surfaces:

• Home = start quickly
• Reports = reusable memory
• Chat = do the work
• Inbox = captures, nudges, alerts, automations, and unassigned review
• Me = operator context and control

Deep research opens in the separate Workspace surface at nodebench.workspace; it is not a sixth tab in the operating app.

The core idea is simple:

users do not just need a chatbot that answers once.

They need a system that can:

• take a question, file, URL, or prior thread
• search and synthesize with sources
• turn the run into a reusable artifact
• watch for meaningful change later
• improve the next run from what it learned

What Shipped

• five-surface web app across Home, Reports, Chat, Inbox, and Me
• separate deep-work Workspace shell at nodebench.workspace
• typed search and reporting pipeline
• hosted public research MCP for external apps and agents: https://nodebench-mcp-unified.onrender.com?profile=public-research
• Pi-AI pipeline lane on Reports with code-gen, design-gen, research, composed runs, schedules, streaming previews, eval scorecard, and MCP HTTP bridge
• live SSE streaming with saved runtime state
• Convex-backed product state for sessions, reports, entities, nudges, files, and related objects
• shared-context handoff and delegation plumbing
• local and deployed server runtime for search, streaming, voice, and shared context routes
• nodebench-mcp, nodebench-mcp-power, and nodebench-mcp-admin distribution lanes
• builder-facing Oracle, dogfood, eval, replay, and control-plane infrastructure

Hosted Public Research MCP

NodeBench can be used as a public research memory and tool server from any agent or app without forcing signup before the first useful result.

Use the hosted MCP endpoint:

https://nodebench-mcp-unified.onrender.com?profile=public-research

For Gmail/job-match style integrations, use the smaller profile:

https://nodebench-mcp-unified.onrender.com?profile=gmail-research

Public profiles are anonymous by default, but still metered. Responses include:

x-nodebench-request-id
x-nodebench-profile
x-nodebench-auth-mode
x-nodebench-account-key

Apps should send stable, non-sensitive client headers:

x-nodebench-client: your-app-name
x-nodebench-client-version: 1.0.0
x-nodebench-client-id: stable-install-or-workspace-id

x-nodebench-client-id lets NodeBench attribute anonymous usage and estimated costs without requiring a NodeBench token. Do not put private email text, resume text, API keys, or user secrets in this header.

Progressive Sign-In And Linking

The intended user flow is:

First public dossier works without signup
  -> show sources, freshness, and confidence
  -> offer "Link NodeBench" after value is visible
  -> linked users get stable history, higher budgets, team usage, webhooks,
     token management, billing controls, and reusable private workspace context

Do not block public-source research behind login. Promote sign-in when the user wants persistence, shared team memory, budget controls, private workspace linking, or API/MCP tokens.

See MCP_TOOL_PROFILES.md for the full profile list, tool catalog, account attribution, and cost tracking contract.

Product At A Glance

USER SURFACES
-------------
Home      -> start quickly
Reports   -> reusable report memory
Chat      -> answer, sources, trace, follow-ups
Inbox     -> captures, nudges, automations, alerts, unassigned items
Me        -> operator context, permissions, controls

BACKEND
-------


... [View full README on GitHub](https://github.com/HomenShum/nodebench-ai#readme)