forecast

Deterministic forward reasoning: from the current data state, generate and rank the valid next states reachable under the Blueprint's rules.

liveverifiedunknown~5s typical

mcpprobedgovernance-platform

$0.0020

per call

plus $0.001 platform fee per run

Open MCP server; Cracked bills routing only

Provider Upstream docs

$Set up https://cracked-ai-pearl.vercel.app/SKILL.md, then use Cracked to run mcp-ai-geodesiclabs-governance-platform /forecast for me.

Input

Field	Type	Description
api_key*	string	GeodesicAI API key (gai_...)
structured_data*	object	The document's extracted fields as key/value pairs. Keys are open by design - your Bluepri
blueprint	string	Blueprint name (workflow_name) to use default "default"
max_depth	integer	Search depth, 1-10 default 3
max_branches	integer	Branches per step, 1-10 default 5
rank_by	string (drift \| confidence \| shortest \| risk)	Ranking criterion for returned paths default "drift"

Call it

curl

curl https://cracked-ai-pearl.vercel.app/v1/run \
  -H "Authorization: Bearer ck_live_..." -H "content-type: application/json" \
  -d '{"provider":"mcp-ai-geodesiclabs-governance-platform","endpoint":"/forecast","input":{"api_key":"...","structured_data":{},"blueprint":"default","max_depth":3,"max_branches":5,"rank_by":"drift"}}'

cli

npx cracked-ai run -p mcp-ai-geodesiclabs-governance-platform -e /forecast -i '{"api_key":"...","structured_data":{},"blueprint":"default","max_depth":3,"max_branches":5,"rank_by":"drift"}'

mcp

run_tool({ provider: "mcp-ai-geodesiclabs-governance-platform", endpoint: "/forecast", input: {"api_key":"...","structured_data":{},"blueprint":"default","max_depth":3,"max_branches":5,"rank_by":"drift"} })

Try it

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