Flow MynaProduct Docs

Reference

Agent Access (MCP)

Your processes, queryable by any agent your company runs. Flow Myna ships a read-only MCP server: connect Claude, Copilot Studio, Bedrock agents — anything that speaks the Model Context Protocol — and they can answer process questions with the same numbers your dashboards show.

Why this exists

Your process data shouldn't only be visible inside our UI. The agents your team already uses — a support copilot, an ops assistant, an internal Claude — become dramatically more useful when they can ask "where are orders getting stuck this month?" and get a real, current, correct answer. The MCP server gives them exactly that: twenty read-only tools over your live process data — aggregates, the process map, and the story of any single case — with no export pipelines and no stale snapshots.

Everything is read-only and deterministic. The tools run the same query engines that power Flow Myna's charts and copilot — no LLM sits between the question and your data, nothing can write, and the numbers match the product UI to the decimal.

Connect in two minutes

Create an API key under Workspace → Data → API Keys (any active key works — keys are workspace-scoped, so the agent sees that workspace's projects and nothing else).

Claude Code:

claude mcp add --transport http flowmyna https://api.flowmyna.com/mcp \
  --header "Authorization: Bearer fm_live_YOUR_KEY"

Cursor, the Claude Agent SDK, or any client that takes an mcpServers block with headers:

{
  "mcpServers": {
    "flowmyna": {
      "type": "http",
      "url": "https://api.flowmyna.com/mcp",
      "headers": { "Authorization": "Bearer fm_live_YOUR_KEY" }
    }
  }
}

Claude.ai, Claude Desktop connectors and ChatGPT authenticate connectors with OAuth rather than an API-key header, so they can't be pointed at the server yet. OAuth sign-in for those clients is on the roadmap; today, use them through Claude Code or an agent framework that sends headers.

Then ask your agent something real:

"Using the Flow Myna tools: what are the top process variants for Sales Orders, and what's our biggest bottleneck?"

A well-behaved agent will call list_projects, learn your schema with describe_project, then answer with concrete counts, shares, and wait times — e.g. "41.6% of orders follow the happy path; the dominant bottleneck is Create Invoice → Clear Invoice at a median 34 days." Ask about one case — "what happened to INC-00224?" — and it finds the object and walks you through every step and every wait.

What agents can ask

Question shapeTool
What projects and data are there?list_projects, describe_project
What does the process look like?get_process_map_summary
What are the main paths? How standardized are we?query_variant_summary
Where does the process get stuck?query_bottleneck_analysis
How long do cases take? Are we getting faster?query_object_duration, query_processing_time_timeline
How long from A to B?query_delay_histogram
How many / average / total?query_headline_stat
Break it down by region/channel/anythingquery_attribute_distribution
Top 10 customers / slowest ordersquery_top_n
Volumes over timequery_volume_timeline
Which steps repeat (rework)?query_rework_analysis
Which activities are most common?query_event_frequency
Where do journeys start and end? How many are still open?query_endpoint_activities
What's different about this group?query_cohort_explain
What happened to order 4711?search_objects, get_object_timeline
Our named business metrics, computed exactlylist_metric_definitions, compute_metric

Every query tool accepts an optional cohort written in plain names — the events a case must (or must not) have, attribute values, completed or in-flight, a timeframe, specific case ids, or one of your saved filters by name — so agents can scope any question: completed cases only, one channel, orders above a value, cases that touched a rework step, last quarter. Cohorts are validated with helpful errors (an unknown name comes back with the valid ones, never as an empty result), free to evaluate, and echoed back as a label so the agent can say exactly what it measured. The product's full structured filter schema is available too for advanced shapes like "A followed by B within 2 days".

Built for object-centric processes

Because Flow Myna is object-centric, agents aren't limited to one case notion. They can ask about Sales Orders, then Deliveries, then Invoices — or across them: order-to-cash cycle time spanning all three, delays between events on different object types, attributes pulled through relationships ("revenue by customer tier"). The describe_project tool hands the agent the full type/relationship graph so it can navigate on its own.

Security model

  • Your existing API keys — nothing new to manage; revoke a key and agent access is gone with it
  • Workspace-scoped — a key can query its workspace's projects, never anything else
  • Read-only by construction — the tool registry contains no write-capable tool, enforced by an automated test on every build
  • Rate-limited — per-key request budget (60/minute), and every query runs under the platform's statement timeouts

Under the hood

  • MCP streamable HTTP transport, stateless, JSON responses — works with every current MCP client
  • Tools return a one-line summary plus the same chart-shaped payload the product renders, so agents can quote numbers and reason over the full result
  • Deterministic SQL builders, shared with the in-product copilot and dashboards — one engine, one set of numbers
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