# How to share context between your team's AI agents

Source: https://beardrive.ai/blog/share-context-between-ai-agents/
Published: 2026-07-30 · Updated: 2026-07-31
Author: Snow Lee · BearDrive

The practical options are pasting context by hand, committing it to a git repo, putting it behind an MCP server, or syncing a shared folder to every machine. Pasting doesn't survive the session, a repo only reaches people who use git, and an MCP server means one more service to run. A synced folder is the only one where the files stay local, so every agent reads them without an integration.

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Every team that adopts AI agents hits the same wall about a month in. One person's agent knows the pricing rationale, another's knows the migration plan, and neither knows what the other knows. The context exists — it's just trapped in whoever's session produced it.

## Why does context stay stuck in one person's session?

Because agent memory defaults to being local and private. Claude Code reads `CLAUDE.md` from the working directory. Cursor reads its rules file. Codex reads `AGENTS.md`. Each one is a file on one laptop, and nothing moves it anywhere.

That's a reasonable default — your notes are yours — but it means the useful byproduct of every session (the summary, the decision, the research) lands in a directory nobody else can see. The knowledge was created. It just wasn't shared.

## What are the actual options?

**Paste it.** Copy the relevant context into the next session. It works, it costs nothing, and it survives exactly as long as the conversation does. Fine for one person on one project; unworkable the moment two people need the same thing.

**Commit it to a repo.** Put the markdown in git next to the code, and every engineer's agent has it. This is the right answer when the context _is_ about the code. It stops working when the people who own the context — sales, support, the founder — don't use git. A workflow that requires a pull request excludes most of the company from the knowledge base.

**Put it behind an MCP server.** Give the agent a tool that queries a shared store. This is genuinely the right shape when the data lives somewhere an agent can't read directly: a database, a CRM, a ticket tracker. For markdown files it's a lot of machinery — a service to run, auth to configure, a round trip on every read, and nothing works offline.

**Sync a folder.** Keep the context as files in one folder, and keep that folder identical on every teammate's machine. Every agent already reads files from disk, so nothing needs an integration: the agent doesn't know or care that the folder is shared.

## What does a shared folder actually buy you?

The agent-facing part is that reads are free. No tool call, no network hop, no permissions dance — the files are simply _there_, the way CLAUDE.md is there. An agent that can read a folder can also write to it, so the summary your agent produced at 2pm is on your colleague's disk before their next session starts.

The human-facing part matters just as much. Non-engineers can open the folder in Finder, drop in a PDF, and edit a document, and the same content reaches every agent on the team. That's the difference between a knowledge base the whole company maintains and one three engineers maintain.

The part people underestimate: versioning. Shared context rots. Six months in, the question is never "what does this document say" but "is this still true, and who changed it." Per-file history and attribution turn a stale wiki into something you can audit.

## What's the catch?

Sync is a real distributed-systems problem, and anyone who tells you otherwise hasn't run it in production. Two people edit the same file offline; both come back online. You want to know exactly what your tool does there — keep both versions, or silently pick one. Ask before you adopt.

The second catch is scope. A folder that syncs everything eventually syncs something that shouldn't leave a laptop. Whatever you use should let you sync part of a folder, not just all of it.

BearDrive is our answer to this: mount a folder, and it stays in sync across every device and teammate, with per-file history and public share links when you want them. It's open source, and it's what the rest of this blog is mostly about.

## Questions

**Can two AI agents share the same memory?**

Yes, if the memory is files rather than a vendor's internal store. Every major coding agent reads plain files from the working directory, so a folder that syncs to each machine gives Claude Code, Codex, and Cursor the same context with no integration between them.

**Do I need an MCP server to give an agent shared context?**

No. MCP is the right answer when the data lives in a system the agent can't reach — a database, a ticket tracker, an API. For markdown and documents, files on disk are simpler, work offline, and need no server running.

**Where should a team's agent memory live?**

In one folder per project that every teammate has locally, versioned so you can see who changed what. Keep it out of the code repo if non-engineers need to write to it, since a git workflow excludes most of a company.