NeoHive is the context engineering layer that makes Claude, Copilot, Cursor, and every coding agent aware of your actual codebase and documentation via MCP. Grounded answers, not generic suggestions.
Free during beta No credit card required Enterprise pilots available
Same question. Two very different answers.
Your agent recommends a deprecated library because it doesn't know your monorepo moved off it six months ago.
import { legacyAuth } from '@old/sdk'
// ^ removed in v4.2, agent unawareIt confidently calls functions that don't exist in your codebase, or passes the wrong argument shapes.
db.users.findByEmail(email)
// ^ hallucinated; we use findOne({ email })It ignores your style guide, naming patterns, error-handling philosophy and team-specific lint rules.
try { ... } catch (e) { console.log(e) }
// ^ we throw AppError in this repoAgent greps through the repo one file at a time and still ends up guessing.
One tool call returns a grounded answer, with real files and ADRs cited inline.
What teams see in the first month
NeoHive sits between every coding agent your team uses — and your repos, docs, and tickets. Agents query and stream answers back on the left; sources feed in from the right.
NeoHive runs as a Docker container in your environment and connects your AI tools to your actual codebase via MCP.
Point NeoHive at your repos and documentation. One CLI command. Supports code, markdown, PDFs, and Jira.
NeoHive indexes your codebase, maps dependencies, and builds a semantic understanding of your architecture and conventions.
Add NeoHive as an MCP server in Claude, Cursor, or Copilot. Your team keeps their workflow. AI answers get grounded in your code.
Maps your codebase into a queryable graph of symbols, files, and dependencies, so agents can find what they need by meaning, not by string match.
NeoHive runs entirely in your environment.
Runs in your VPC or on your machine. All embedding and retrieval happens locally inside the container.
The container makes no external network requests. The only external traffic is your existing AI tool API calls.
Deploy on your infrastructure from day one. Air-gapped and VPC-compatible for regulated environments.
Respects your access controls. Engineers only see answers derived from content they're authorised to access.
Local Docker container. Zero outbound data. All embedding local. VPC-compatible.
The only external traffic is your existing AI tool API calls, which your team is already making.
A single Docker container, running in your infrastructure, exposed as a native MCP server. The admin console is where you define projects, wire up hives of repos and docs, and watch context reach every connected agent.
"how do we rate-limit the /auth endpoint?"Cursor · 2m ago"find usages of deprecated SDKv3"Claude · 14m ago"what's our error-handling convention?"Copilot · 1h agoJoin the engineering teams piloting NeoHive. Onboard in an hour, see results on your first PR.
Free during beta No credit card required Enterprise pilots available
NeoHive is a context engineering layer for AI coding tools. It runs as a local Docker container that indexes your codebase, documentation, and Jira, then serves that context to Claude, Cursor, GitHub Copilot, Windsurf, and ChatGPT via the Model Context Protocol (MCP). Your AI tools go from giving generic textbook answers to giving grounded, codebase-specific responses that reference your actual architecture, internal APIs, and conventions.