Flowgraf MCP Server

Create a NEW architecture diagram from a graph that YOU author, and get back a shareable, editable canvas URL plus a rendered SVG and Mermaid. You produce only the SEMANTICS — nodes, the groups (VPC/cluster/...) they live in, and the directed edges between them. You do NOT lay anything out: never send x/y/position/pinned. A deterministic layout engine computes all geometry and an icon layer picks the pictures from each node's kind. kind.catalog is one of aws | gcp | azure | k8s | saas | generic, each with rich per-catalog kind.types (e.g. aws:lambda, gcp:bigquery, azure:cosmos_db, k8s:deployment, saas:kafka): - "aws" (api_gateway, lambda, s3, rds, dynamodb, sqs, bedrock, kinesis, fargate, eventbridge, aurora, ...). - "gcp" (compute_engine, gke, cloud_run, cloud_sql, spanner, firestore, bigquery, pubsub, dataflow, vertex_ai, ...). - "azure" (virtual_machine, aks, app_service, functions, blob_storage, sql_database, cosmos_db, service_bus, event_hubs, key_vault, ...). - "k8s" (pod, deployment, statefulset, daemonset, job, cronjob, service, ingress, configmap, secret, hpa, ...). - "saas" for hosted third-parties (redis, postgresql, mysql, mongodb, kafka, stripe, twilio, auth0, github, cloudflare, ...). - "generic" primitive when nothing branded fits: service, database, cache, queue, user, external_system, storage, gateway, function, note. - "generic" FLOWCHART kinds for processes/flowcharts: process, decision, terminator, data, document, subprocess. edge.kind is one of: request, response, async_event, data_flow, dependency, network, generic. WORKED EXAMPLE — a user hitting an API in a VPC that talks to Postgres: { "title": "Web API", "domain": "cloud_architecture", "graph": { "groups": [{ "id": "g_vpc", "label": "VPC", "type": "vpc" }], "nodes": [ { "id": "n_user", "label": "User", "kind": { "catalog": "generic", "type": "user" } }, { "id": "n_api", "label": "API", "kind": { "catalog": "aws", "type": "api_gateway" }, "parentId": "g_vpc" }, { "id": "n_db", "label": "Postgres", "kind": { "catalog": "aws", "type": "rds" }, "parentId": "g_vpc" } ], "edges": [ { "id": "e1", "source": "n_user", "target": "n_api", "kind": "request" }, { "id": "e2", "source": "n_api", "target": "n_db", "kind": "data_flow" } ] } } Returns { diagramId, url, svg, mermaid, version }. Give the user the url — opening it shows the same diagram on an editable canvas (anonymous; it's theirs to claim by signing in). To change the diagram afterwards, use get_diagram then edit_diagram.

Fetch a diagram's raw IR (nodes, groups, edges with their real ids) and its current `version`. Call this before edit_diagram so your ops reference ids that actually exist and you pass the correct baseVersion. Returns { diagram, version }.

Apply a list of operations to an EXISTING diagram. The ops re-use this tool's op vocabulary; you author them, we validate + apply + re-layout + re-render. ALWAYS call get_diagram(diagramId) first: it returns the current ids and the `version`. Pass that version as `baseVersion`. If the diagram changed since you fetched it, you get a STALE_VERSION error telling you the current version — refetch with get_diagram, recompute your ops, and retry. The operations (each element of `ops`): - add_node { op, node:{ id, label, kind, parentId? } } - remove_node { op, id } (also drops edges touching the node) - update_node { op, id, patch:{ label?, kind?, parentId?, metadata? } } - add_edge { op, edge:{ id, source, target, kind, label?, directed? } } - remove_edge { op, id } - update_edge { op, id, patch:{ source?, target?, label?, kind?, directed? } } - add_group { op, group:{ id, label, type, parentId? } } - remove_group{ op, id } - move_to_group { op, nodeId, groupId } (groupId null un-nests the node) - set_layout { op, patch:{ direction?, spacing? } } - insert_between { op, newNode:{ id, label, kind, parentId? }, sourceId, targetId, inKind?, outKind? } insert_between IS THE KEY OP for "add X between A and B" requests. It splices newNode onto the existing A→B edge: removes that edge, adds the node, and wires A→newNode→B so the connection re-routes through it automatically. WORKED EXAMPLE — "add a Redis cache between the API and the DB" on the diagram above: 1) get_diagram(diagramId) → shows nodes n_api, n_db and version 1. 2) edit_diagram({ diagramId, baseVersion: 1, ops: [ { "op": "insert_between", "sourceId": "n_api", "targetId": "n_db", "newNode": { "id": "n_redis", "label": "Redis", "kind": { "catalog": "saas", "type": "redis" }, "parentId": "g_vpc" }, "inKind": "request", "outKind": "data_flow" } ] }) The API→DB edge is gone and now flows API→Redis→DB. Never send x/y/position — geometry is computed for you. Node kinds: catalog ∈ {aws, gcp, azure, k8s, saas, generic} with rich per-catalog types (e.g. aws:lambda, gcp:bigquery, azure:cosmos_db, k8s:deployment, saas:kafka), plus generic flowchart kinds (process, decision, terminator, data, document, subprocess). Returns { url, svg, mermaid, appliedOps, version }.