What inputs does save_agent accept?

agent_id (string, optional): Omit to create a new agent; pass an existing agent's id (from save_agent/list_agents/get_agent) to update it. name (string, required): Human-readable label. goal (string, required): What this agent is trying to accomplish — drives an autonomous agent's AI-directed team, and documents intent for a workflow agent's fixed steps. tickers (array, required): US tickers this agent operates over. Normalised to uppercase. agent_type ("workflow" | "autonomous", required): STRUCTURAL and immutable. "workflow" = fixed step recipe, free/deterministic, requires `steps`. "autonomous" = AI-directed team, charged, may set `managed_model`. when ("manual" | "schedule", required): Trigger mode. "manual" fires only via run_agent/the UI; "schedule" requires the `schedule` object. schedule (object, optional): Required when when="schedule"; ignored otherwise. managed_model (string, optional): Managed-lane model override for agent_type="autonomous" only (e.g. when no BYO key is connected). Omit to use the account default. steps (array, optional): Fixed step recipe for agent_type="workflow". Required + non-empty when CREATING a workflow agent; must be omitted for agent_type="autonomous".

Which Valuein plans include save_agent?

Available on the free tier (token required) and on Pro and Institutional. Not point-in-time safe.

Discovery

Save Agent

save_agent

Benchmark and above

Create or update a standing agent — a saved {goal + tickers + schedule} that fires either a fixed step recipe (agent_type="workflow", free/deterministic) or an AI-directed team (agent_type="autonomous", charged — settles against the owner's BYO key first, falling back to the m...

Example Call

example_call.pypython

# Using the Valuein MCP server from Python (via MCP SDK)# Or call directly from Claude / Cursor after setup result = await client.call_tool(    "save_agent",    arguments={    "name": "EXAMPLE",    "goal": "EXAMPLE",    "tickers": [],    "agent_type": "workflow",    "when": "manual"})print(result)

Direct tool call:save_agent(...)

Inputs

Parameter	Type	Required	Description
`agent_id`	string	optional	Omit to create a new agent; pass an existing agent's id (from save_agent/list_agents/get_agent) to update it.
`name`	string	required	Human-readable label.
`goal`	string	required	What this agent is trying to accomplish — drives an autonomous agent's AI-directed team, and documents intent for a workflow agent's fixed steps.
`tickers`	array	required	US tickers this agent operates over. Normalised to uppercase.
`agent_type`	"workflow" \| "autonomous"	required	STRUCTURAL and immutable. "workflow" = fixed step recipe, free/deterministic, requires `steps`. "autonomous" = AI-directed team, charged, may set `managed_model`.
`when`	"manual" \| "schedule"	required	Trigger mode. "manual" fires only via run_agent/the UI; "schedule" requires the `schedule` object.
`schedule`	object	optional	Required when when="schedule"; ignored otherwise.
`managed_model`	string	optional	Managed-lane model override for agent_type="autonomous" only (e.g. when no BYO key is connected). Omit to use the account default.
`steps`	array	optional	Fixed step recipe for agent_type="workflow". Required + non-empty when CREATING a workflow agent; must be omitted for agent_type="autonomous".

Output Fields

agentcreated

Example Response

Illustrative

response.jsonjson

{  "agent": null,  "created": null}

Shape only — field names match the live schema; values are placeholders, not real filings. See MCP server for the structured response shape.

Notes

Available from the Benchmark plan and above.

Try this tool

Get token All tools

CategoryDiscovery

PIT-safeNo

Min planBenchmark

Inputs9 (5 required)

Plan Access

Sample (guest)

Not included

Benchmark (token)

Available

Pro

Available

Institutional

Available

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Resources

Point-in-Time methodology →Parquet schema reference →Bulk Data API reference →Python SDK guide →

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