Skip to content
Knowledge Base

Everything your team learns with AI, searchable and reused

CloudByte AI captures prompts, observations, commits, decisions and CLAUDE.md files from every developer, stores them in a context-aware vector database and feeds them back into future prompts through an MCP service.

Book DemoStart free
Sources

Captured from every developer, aggregated per project

The agent picks up knowledge where it is created, on every developer machine, and merges it into one Knowledge Base for each project. Nobody has to write anything down.

  • Prompts

    Every prompt developers send, with the session it belonged to and what came out of it.

  • Observations

    What the AI noticed while working: gotchas, edge cases and how parts of the code really behave.

  • Git commits

    Each commit with an AI summary, linked back to the sessions and prompts that wrote it.

  • Decisions

    Choices made during a session and the reasons behind them, captured as they happen instead of lost in chat.

  • CLAUDE.md files

    Every developer's CLAUDE.md for each repository, brought together into one view of the project's rules.

  • Related repositories

    Linked repositories and services, so knowledge follows the code across repository boundaries.

03MCP service

An MCP service that feeds knowledge back into every prompt

The Knowledge Base runs as an MCP service. It loops what each developer has learned back into their future prompts, and brings in prompts and fixes from teammates who worked on similar problems. Any MCP-compatible tool can connect to it, not just CloudByte AI.

  • Feeds each developer's own history back into their future prompts
  • Shares cross-developer prompts and fixes for similar work
  • Works with any MCP-compatible tool or agent, inside or outside CloudByte AI
  • Each connection only reads the projects it is allowed to
How it works

From a single session to team knowledge

Four steps turn what one developer learns into context the whole team, and its tools, can use.

  1. 01

    Capture

    The agent on each machine captures prompts, observations, commits, decisions and CLAUDE.md files as developers work.

  2. 02

    Aggregate

    Captures from every developer are merged per project and linked to its related repositories.

  3. 03

    Store

    Everything lands in a context-aware vector database, with its source and context attached.

  4. 04

    Reuse

    Developers search it, and the MCP service feeds it back into future prompts across the team.

The learning loop

One fix, reused by the whole team

Here is how a decision made by one developer on Monday reaches another developer working in a different repository on Thursday.

  1. 1
    Decision capturedMon 10:12 · priya · payments-api

    Fixes duplicate refunds and decides that every refund must carry an idempotency key.

  2. 2
    Commit linkedMon 10:40 · priya · payments-api

    Commit a1f3c9 is summarized and linked to the session, the prompt and the decision.

  3. 3
    New promptThu 15:05 · alex · checkout-web

    Asks the AI to add partial refunds to checkout, in a related repository.

  4. 4
    Context addedThu 15:05 · MCP service

    Priya's decision and commit are added to Alex's prompt, so the fix is reused instead of rediscovered.

Knowledge you can trust

  • Linked to its source

    Every answer shows the prompt, commit or decision it came from.

  • Labelled by trust

    Verified, Source, AI generated and Inferred labels show how far to rely on each result.

  • Inside your boundaries

    Knowledge stays in your organization, and people only see the projects they can access.

  • Scanned before it is stored

    Prompt scanning runs before capture, so credentials and personal data your rules catch stay out.

FAQ

Knowledge Base questions, answered

How knowledge is captured, stored, searched and shared through the MCP service.

Ask us anythingBook a demo

Prompts, observations, git commits, decisions, CLAUDE.md files and related repositories, captured from every developer on the team and aggregated per project.

No. The agent captures knowledge as developers work and merges it per project. Nobody has to write documentation for the Knowledge Base to fill up.

So search works on meaning instead of exact words. Each entry is stored with its context, such as the project, repository, files, developer and date, which lets the right knowledge surface even when it was phrased differently.

Anything the team has captured, in plain words. Results come from every source at once, each linked to where it came from and labelled by trust, and your search history is kept so you can pick up where you left off.

The Knowledge Base runs as an MCP service that AI tools call while they work. It feeds each developer's own history back into their future prompts, and adds prompts and fixes from teammates who worked on similar problems.

Yes. Any MCP-compatible tool or agent can connect, not just the CloudByte AI agent. Each connection only reads the projects it has been given access to.

Knowledge stays inside your organization. People and connected tools only see the projects they have access to.

Prompt scanning from AI Security runs before anything is captured, so credentials and personal data your rules catch never reach the Knowledge Base.

The project Knowledge Base is included in the Team plan and in Enterprise.

Stop solving the same problem twice.

Install the agent once per laptop and every session starts adding to your team Knowledge Base within minutes.

Book DemoStart free
  • Free for up to 5 developers
  • 10-minute setup
  • Your Anthropic key, your spend