Let agents drive the flow API over MCP
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The engine now speaks MCP at /mcp, with a built-in OAuth 2.1 authorization server in front of it: an agent registers itself, sends a human to the browser to approve it, and exchanges the resulting code for a token. PKCE is required, codes are single-use and stored only as hashes, the browser is redirected to the URI that was registered rather than the one asked for, and refresh tokens rotate so that replaying a spent one revokes the whole line. Twenty tools cover reading, building, publishing and running flows, and each one calls the same REST endpoint the dashboard calls, in-process, carrying the caller's own token. That keeps one description of what a flow is and what may be done to it — validation, the draft/publish split, the version check — and means an agent can do nothing a person could not do in the browser. Agent tokens are RS256 with a keypair of their own rather than the secret that signs browser sessions, so deleting the key withdraws every agent without logging anyone out, and deps.decode_token grew the branch that trusting a second issuer will need when the hosted login arrives. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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@@ -75,7 +75,13 @@ external interfaces. See `docs/architecture/structure.canvas` → *Backend – M
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- [ ] Test nodes: a small node dragged onto an existing one, smoke or unit, blocking
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deployment on failure
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- [ ] User management scoped per flow and per data set
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- [ ] LLM interface for natural-language flow authoring
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- [x] MCP server over the same API: agents authenticate through a built-in
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OAuth 2.1 authorization server (dynamic registration, PKCE, rotating
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refresh tokens) and drive the flow API through 20 tools. Tokens are
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RS256, signed with their own keypair, so the set can be revoked on its
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own — and an additional issuer is one branch in `deps.decode_token`,
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which is the seam remote access needs later
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- [ ] LLM interface for natural-language flow authoring beyond the MCP tools
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## Phase 2 — Backend: processing
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