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DevVis captures everything that happens across your development workflow and stores it in a searchable knowledge graph. No manual notes. No context switching. Just ask your AI assistant what happened, why something changed, or what’s in progress — and get a grounded answer.

Three ingestion points

DevVis automatically captures activity from the three places where development actually happens:

Claude Code

Sessions, plans, tasks, token usage, and session summaries — captured via hooks on the developer’s machine.

GitHub

Pushes, pull requests, and code reviews — captured via repository webhooks.

Linear

Issues, comments, projects, and project updates — captured via workspace webhooks.
All three streams feed into the same knowledge graph, so you can ask questions that span AI activity, code changes, and project management in a single query.

How it works

Claude Code hooks          GitHub webhooks         Linear webhooks
  │                            │                        │
  ├── SessionStart             ├── push                 ├── Issue created/updated
  ├── ExitPlanMode             ├── pull_request         ├── Comment
  ├── TaskCreate               └── pull_request_review  ├── Project
  ├── TaskUpdate                                        └── ProjectUpdate
  └── Stop


devvis CLI (local enrichment: git identity, transcript, token usage)

  └──────────────────────────────────────────────────────────┐

                                               DevVis API → Redis Queue


                                               Event Worker → Knowledge Graph (Neo4j)


                                               MCP Reader → Claude clients

Query from any MCP-enabled tool

Once events are in the graph, you retrieve context through the MCP Reader — available in any tool that supports the Model Context Protocol, including Claude Code, Claude Desktop, OpenAI Codex, and others. Ask things like:
  • “What did the team deliver this week? Summarize completed issues, merged PRs, and any blockers.”
  • “What is our average cycle time from opening an issue to merging the PR? Which items are taking the longest, and why?”
  • “Is the team on track to finish the current sprint? Which issues haven’t had any activity in the last 3 days?”
  • “How much of our engineering effort is going to new features versus bug fixes versus infrastructure? Has that changed compared to last month?”
  • “How much of our codebase is being built with AI assistance? What is the concrete return on that investment?”
  • “How efficient is our code review process? How many PRs required rework, and what are the most common reasons?”

Get started

GitHub and Linear ingestion are configured via webhooks in your repository and workspace settings — no additional software needed on your machine.