Everything your AI needs to actually do things
1,000+ integrations with just-in-time tool loading, delegated auth, isolated sandboxes, and parallel execution.
- Northbeam
- Hollow
- Datafold
- Craftral
- Ohm
- Ardent
- Kestrel
- Lumen Bay
- Fieldnote
- Parallel
- Sable
- Overtone
- Riverbend
- Quill
- 1. Fetch open issues
- 2. Rank by severity
- 3. Create board task
- ! project slug required
- ! board id must be set
- AGENT
- Claude
- TOOLKITS
- 4 connected
- SANDBOX
- isolated
channels = run_tool("CHAT_LIST_CHANNELS")
for ch in channels:
msgs += run_tool("CHAT_FETCH", channel=ch)ranked = classify(msgs, by="urgency") digest = summarize(ranked[:15])
Your agent thinks fast.
Give it tools that keep up.
- Fetch open issues
- Rank by severity
- Create board task
- ✓ project slug found
- ▸ board id needed
Discovery with judgment
Context is precious — spend it on the task. Tools surface on demand, matched to what the agent is trying to do.
- Tools resolved by intent, not configuration
- Execution plans proposed for multi-step work
- Guardrails built in, so the first try lands
Tools that improve themselves
Live traffic teaches the platform. When a call pattern fails somewhere, the fix rolls out everywhere — usually before you hit it.
- Accuracy tuned by millions of live calls
- Optimizations that follow your usage patterns
- API-stable, agent-optimized surface
List my open PRs and summarize what needs review.
I need access to your repos to fetch PRs.
Auth you never think about
Stop debugging OAuth flows. Connection happens inline, exactly when the agent needs it, scoped to exactly what it needs.
- Managed OAuth for every connector, out of the box
- Inline auth triggered by user intent, not pre-config
- Permission scopes that tighten as you go
msgs = []
for ch in run_tool("CHAT_LIST_CHANNELS"):
msgs += run_tool("CHAT_FETCH", channel=ch)
digest = cluster_and_rank(msgs) # 2,183 msgs
run_tool("MAIL_SEND_MESSAGE",
to=me, body=digest) # → 200 SentProgrammatic execution
Heavy work runs in an isolated sandbox: your agent writes code that calls tools in loops, filters results, and returns just the answer.
- Isolated runtime per session, zero setup
- Tool calls composable from real code
- Big data stays out of the context window
One product, every workflow
Do it all from one chat
Turn any MCP client into an agent that reaches your real tools. Every tool arrives signed in, tuned, and ready — nothing to configure.
Five lines from model to agent
The intelligence is already there — what's missing is reach. Hand a session its tools and let it work.