LIVE ENDPOINT
https://api.misata.studio/mcp
Connect to this endpoint to inspect the live schema for cancel_generation and invoke it with your own arguments.
Indexed input schema
{}Risk classification
Inferred read-only · medium confidence · heuristic, not a guarantee.
- No write-capable action terms were found; this is not proof that invocation has no side effects.
Parent server
CONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.misata]
url = "https://api.misata.studio/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"misata": {
"type": "http",
"url": "https://api.misata.studio/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: misata
Remote MCP URL: https://api.misata.studio/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"misata": {
"url": "https://api.misata.studio/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"misata": {
"type": "http",
"url": "https://api.misata.studio/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "misata",
"transport": "streamable-http",
"url": "https://api.misata.studio/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
Related tools
whoami— Which account this connection is, and what it may do: signed in with a Studio MCP key or anonymous, the row cap, and whether a model key is available for plain-English requests.plan_dataset— See the tables, sizes and relationships the engine would build, before any rows exist.blueprint_guide— The reference for the engine's full design language (the `blueprint` argument of generate_dataset, start_generation and validate_blueprint): roles, distributions, formulas that read parent columns and draw noise, per-group sequences (seq, lag, cumsum, ar1 drift, random walk), aggregates, event windows, cause-and-effect, lifecycles, with patterns.validate_blueprint— Check a blueprint before generating it: every error said as what to change, the design traps it falls into (a column that will round away, a copy of a value not made yet, a window that counts nothing), its size against your row cap, and a small preview run (a few thousand rows) with the verifier's findings and sample rows, so you can see the data behave before the real call.generate_dataset— Make a verified relational dataset and wait for it: every foreign key checked, dates correctly ordered, declared aggregates and rates exact, before anything is returned.start_generation— Start a generation in the background and return a job_id at once.get_status— Where a start_generation job is.get_certificate— The full certificate for a dataset made by generate_dataset: every claim (stated vs actual), every requirement's status and evidence, realism findings, planted defects/anomalies if any, and the pattern charts.