Context

Self-hosted multiplayer context agent with a private CRM, knowledge base, teammate inbox, and read-only MCP surface.

@context gives one owner a private work context that teammates can contribute to and AI apps can read through a constrained surface.

It is for founders, managers, and operators whose contacts, decisions, reminders, messages, and project knowledge are spread across systems. Teammates can submit updates and check their own receipts. Only verified owner identities receive the private CRM, knowledge, retrieval, and action surfaces.

Agno selects tools from the caller’s identity before the model runs, loads owner-only playbooks at runtime, and exposes one read-only MCP tool to Claude, ChatGPT, Claude Code, Codex, Cursor, and other clients. Run it locally, connect the AgentOS UI, then capture a contact or ask for your daily rundown. The source is public.

Run locally

Prerequisites: Docker and an OpenAI API key.

git clone https://github.com/agno-agi/context.git && cd context

cp example.env .env
# Set OPENAI_API_KEY, OWNER_ID, OWNER_NAME, and OWNER_TIMEZONE in .env

docker compose up -d --build
curl http://localhost:8000/health

Open the API at localhost:8000/docs. OWNER_ID decides who receives the private owner surface. In AgentOS and private Slack DMs, every other verified caller receives the private guest surface.

Connect the AgentOS UI

1. Open os.agno.com and sign in with an identity listed in OWNER_ID.
2. Choose Connect OS → Local.
3. Enter http://localhost:8000, name it Local Context, and connect.
4. Open Context under Agents and try a prompt from the examples below.

Connect MCP clients

The MCP endpoint exposes one tool, use_context, for retrieving and preparing the owner’s private context. Filing, learning, acknowledgement, drafts, Slack sends, and other mutations are absent from this surface.

uvx agno connect

The command detects supported local clients, preserves their other MCP entries, registers http://localhost:8000/mcp, and verifies the connection. Undo the registrations with uvx agno disconnect.

Local MCP is keyless in development. Anything that can reach the port can read the owner’s context through use_context. Keep it on a trusted machine and network. See docs/MCP.md for production OAuth and per-client setup.

How it works

@context is one Agno agent that captures, files, retrieves, and prepares working context. In production, AgentOS verifies HTTP identities from JWTs. Slack verifies signed events and maps their authors to user IDs. Explicit local development trusts the caller-supplied user_id.

Caller	Effective surface
Owner in AgentOS or a private Slack DM	Full configured Context surface
Guest in a private run or DM	submit_update, caller-scoped my_updates, and caller-scoped learning
Anyone in a shared Slack room	submit_update only
Owner-approved MCP client	Fresh, private, read-only use_context calls

The built-in playbooks help the owner retrieve and prepare context:

Playbook	Ask	What you get
Rundown	”What’s on today?”	Queued teammate updates, due reminders, stored meetings, and relevant Gmail or Slack context when configured
Week plan	”What’s my week?”	Priorities for the week. When Slack is configured, runs Sunday evening and lands in your Slack DMs
Prep	”Prep for my 2pm with Kyle”	A pre-meeting brief: who they are, notes, past threads, what’s still open, and public background for contacts you don’t know yet

Playbooks live in skills/, one SKILL.md per folder. The shipped set also includes process-today, research, and knowledge-review. When Slack is configured, scheduled daily and weekly playbooks DM their results to the owner.

Context sources

Most sources use Agno context providers that expose query_<id> for reads and a source-scoped update tool where writes are enabled. The workspace source exposes list_files, search_content, and read_file directly.

Source	Access	Enabled by
crm	Read and write	Always on
knowledge	Read and write	Always on
workspace	Read	Always on
web	Read	Always on
slack	Read; owner-confirmed sends	SLACK_BOT_TOKEN
gmail	Read; draft create and update only	Google OAuth credentials and a Gmail token

The crm source stores contacts, projects, meetings, reminders, notes, and queued updates in Postgres. The knowledge source stores specs and research notes on the filesystem by default and can use a private Git repository in production.

Security

The toolset is chosen in code from the request identity before the model runs. A private guest can append to the owner’s queue with submit_update and read only their own receipts with my_updates. Shared Slack rooms expose only submit_update. Guests cannot access the owner’s CRM, knowledge base, inbox, queue, or action tools. Each caller’s memory is scoped to their verified identity.

Owner actions are narrow. update_slack sends exact text only after explicit approval. update_gmail can create or update a draft and has no send capability. After a provider, workspace, or rundown read, the current run becomes read-only. Make any follow-up mutation as a fresh private request.

@context runs locally or in your own cloud. Its CRM and inbound queue live in Postgres, and its knowledge base lives on the filesystem or in a private Git repository. Prompts and retrieved material are processed by the model and provider services you configure. See docs/SECURITY.md.

Deploy to Railway

@context runs anywhere that runs a Docker container. For a quick deployment, scripts/railway/up.sh runs @context and Postgres on the same private network. It reads credentials from .env.production and creates the public domain you connect to in the AgentOS UI.

Prerequisites: Railway CLI installed and railway login completed.

1. Create a production env

   cp .env .env.production
   

   The deploy scripts read .env.production first and fall back to .env.

2. Deploy

   ./scripts/railway/up.sh
   

   The script creates your public domain, then pauses and waits while you mint the JWT verification key.

3. Mint your JWT key

   Token-Based Authorization is on by default. Without a JWT_VERIFICATION_KEY in .env.production, the AgentOS will not serve traffic. That is the safe default for an agent that holds your work context. You can also issue and verify your own JWT.

   1. Open os.agno.com, click Connect OS → Live, and paste the domain the script printed.
   2. Turn on Token-Based Authorization and click Connect.
   3. Copy the public key into .env.production as JWT_VERIFICATION_KEY.
   4. Back in the terminal, press Enter. The script reads the key and deploys the service.
4. Verify

   railway logs --service agent-os
   

   Open https://<your-domain>/docs to confirm the API is serving.

If you add or update values in .env.production, sync them with ./scripts/railway/env-sync.sh. After code changes, redeploy with ./scripts/railway/redeploy.sh, or connect the repo in the Railway dashboard to auto-deploy on push.

Point MCP clients at production

Production connections use MCP OAuth. scripts/railway/up.sh generates MCP_CONNECT_SECRET when it is missing. A client connects by URL, and you approve it once on a consent page by entering that secret.

uvx agno connect --url https://<your-domain>

The command wires Claude Code, Codex, Cursor, and Claude Desktop and prints each client’s sign-in step. In claude.ai or ChatGPT, add https://<your-domain>/mcp through the app’s custom connector flow, leave optional OAuth client credentials empty, and approve the consent page with MCP_CONNECT_SECRET. The AgentOS UI uses its separate control-plane JWT. Rotating AGENTOS_MCP_SIGNING_KEY revokes every issued token; rotating MCP_CONNECT_SECRET gates future consents.

See docs/MCP.md for the consent flow, per-client specifics, and ChatGPT and Claude on the web.

Back the knowledge base with Git

Local runs store the knowledge base in a gitignored knowledge/ folder. In production, back it with a private Git repo: create one, mint a fine-grained token with read and write access to its contents, and add both to .env.production:

KNOWLEDGE_REPO_URL=https://github.com/you/your-context.git
KNOWLEDGE_GITHUB_TOKEN=ghp_...

Then sync with ./scripts/railway/env-sync.sh. Every update commits and pushes, so the git history is your audit trail. See docs/KNOWLEDGE.md.

Connect to Slack

With Slack configured, teammates can @-mention @context to leave you updates, you can DM it for private conversations, and the scheduled daily rundown and weekly plan land in your DMs.

1. Create a Slack app from the manifest in docs/SLACK.md.
2. Copy the Bot User OAuth Token and Signing Secret.
3. Set SLACK_BOT_TOKEN and SLACK_SIGNING_SECRET in .env or .env.production.
4. Restart the application.

Local runs need a public URL for Slack’s callbacks, so use an ngrok tunnel. Once you deploy, repoint the app’s /slack/events and /slack/interactions request URLs at your Railway domain.

Connect Gmail

Connect Gmail to ground rundowns and preparation in your inbox. Set GOOGLE_CLIENT_ID, GOOGLE_CLIENT_SECRET, and GOOGLE_PROJECT_ID, then mint the consent token once with python scripts/google_mint_tokens.py. See docs/GOOGLE.md.

Example prompts

Use the AgentOS UI or a private Slack DM for prompts that write context:

• Add Dana Reyes, Head of Platform at Acme, [e-mail]. Remind me to send her the integration spec next Tuesday.
• Write up a decision: we’re standardizing on Agno.

Use any connected interface for retrieval and preparation:

• Who do I know at Acme?
• What’s on today?
• Prep for my 2pm with Kyle.
• What in my knowledge base needs attention?

Run evals

@context comes with model-backed behavioral evals in evals/. They exercise guest boundaries and adversarial attempts to reach owner data. Deterministic policy and authorization checks live in tests/.

./scripts/venv_setup.sh

.venv/bin/python -m evals --tag smoke
.venv/bin/python -m evals --tag release
.venv/bin/python -m evals --name guest_cannot_read_the_crm

Source

The GitHub repo has the full detail:

Guide	Covers
AGENTS.md	Architecture, key files, and conventions for coding agents
docs/SECURITY.md	The owner/guest model, read boundary, and action controls
docs/MCP.md	Per-client MCP setup and production MCP OAuth
docs/SLACK.md	The app manifest, identity resolution, and moving to production
docs/KNOWLEDGE.md	The knowledge base and Git backing
docs/CRM.md	The crm schema, filing rules, and the write boundary
docs/GOOGLE.md	Gmail setup
docs/NETWORK.md	How a team’s contexts talk to each other