counterfactual-forge
Enables AI agents to fork plans into counterfactual worlds, score them with rubrics and simulations, detect contradictions, measure regret, and merge a winner with a full audit trail.
README
Counterfactual Forge
What-if branching for AI agents. Fork a plan into counterfactual worlds, score them with rubrics + simulated outcomes (confidence intervals), detect contradictions, measure regret, and merge a winner — with a full audit trail.
Expose the whole loop as an MCP server so Cursor / Claude / any MCP client can fork → score → merge from tools.
Packages
| Package | Role |
|---|---|
@counterfactual-forge/core |
Deterministic domain model + fork/score/compare/merge/export |
@counterfactual-forge/mcp-server |
Stdio MCP tools (cf_*) |
@counterfactual-forge/cli |
cff / counterfactual-forge CLI |
@counterfactual-forge/studio |
Vite studio to inspect world trees & scores |
Quick start
git clone https://github.com/SanjoyDat1/counterfactual-forge.git
cd counterfactual-forge
npm install
npm run build
npm test
npm run cff -- demo --out /tmp/cff-report.md
Studio UI:
npm run studio
# → http://localhost:5173
MCP (Cursor)
Add to your MCP config (e.g. Cursor mcp.json):
{
"mcpServers": {
"counterfactual-forge": {
"command": "node",
"args": [
"/ABSOLUTE/PATH/TO/counterfactual-forge/packages/mcp-server/dist/index.js"
]
}
}
}
Or after publishing / linking:
{
"mcpServers": {
"counterfactual-forge": {
"command": "npx",
"args": ["-y", "counterfactual-forge-mcp"]
}
}
}
Tools
| Tool | Description |
|---|---|
cf_create_session |
Create session + baseline world from goal + steps |
cf_fork_worlds |
Fork N strategies (aggressive, conservative, parallel, minimal, custom) |
cf_score_world |
Rubric scores + seeded simulation + confidence interval |
cf_compare |
Ranking, regret, contradiction detection |
cf_merge_winner |
Select winner via merge policy |
cf_get_audit_trail |
Append-only audit events |
cf_export_report |
Export json / markdown / mermaid |
Example agent flow
cf_create_sessionwith goal + plan stepscf_fork_worldswithaggressive+conservative(+ optional others)cf_score_worldfor each forked worldcf_compare→ inspect regret & contradictionscf_merge_winnercf_export_report(markdown) for the decision record
CLI
npx cff demo
npx cff create --goal "Ship X" --steps examples/fixtures/auth-redesign-steps.json
npx cff fork --session <id> --strategies aggressive,conservative,minimal
npx cff score --session <id> --world <id>
npx cff compare --session <id>
npx cff merge --session <id> --mode min_regret
npx cff export --session <id> --format mermaid
Sessions are in-memory per process — export / import to persist.
Creative metrics
- Confidence intervals on overall scores (from outcome simulation percentiles)
- Regret — how many points worse than the best alternative
- Contradiction detection across assumptions / risks / strategy tags
- Mermaid world-tree export embedded in Markdown reports
Architecture
See docs/ARCHITECTURE.md and docs/PLAN.md.
Development
npm run typecheck
npm run test:coverage # core ≥80%
npm run build
Logging uses stderr only (CFF_LOG_LEVEL=debug|info|warn|error|silent) — safe for MCP stdio.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.