Poker Solver

Post-session, educational heads-up NLHE decision analysis, with a deterministic Python solver and private MCP transport. This is a constrained river game, not full GTO or a calibrated opponent model. Realistic ranges, omitted betting lines, multiway play and off-equilibrium outcomes require separate assumptions and verification.

What works, and where

Current work and remaining acceptance: GitHub Issues are the only actionable queue. #25 reuse has owner-merged research evidence pending issue disposition; #26 hosted turn remains open for a viable acceptance/release decision. Development scope explains future milestones without repeating PR histories. New solver correctness is not evidence of deployment, useful range modelling or working connected-client tools.

Related MCP server: MCP Poker

Standalone Liar's Dice research

Two-player 吹牛 / Liar's Dice probability enumeration and a restricted one-face CFR prototype are archived under experiments/liars_dice/, including rules, reproducible results and limitations. This experiment is not part of the NLHE solver or the hosted MCP service; Issue #40 tracks the full-rule research.

Local quickstart

Python 3.10+; CI and Render use 3.12.

python -m venv .venv
# Activate .venv (Windows: .venv\Scripts\Activate.ps1)
pip install -r requirements-dev.txt
python -m ruff check poker_spot tests scripts
python -m compileall -q poker_spot scripts
OPENBLAS_NUM_THREADS=1 python -m unittest discover -s tests -v
python -m poker_spot example.json
python scripts/acceptance.py

For PowerShell, set $env:OPENBLAS_NUM_THREADS='1' before the tests. Windows restricted shells may block subprocess fixtures. All routine tests run with local/fictional data and no live provider keys. Numerical/independent benchmark reproduction and full evidence index explain the extra gates and recorded failures; a local green test is not provider acceptance.

MCP and hosted operations

• Local stdio: python -m poker_spot.mcp_server with root plugin.json, mcp.json and skills/river-review/.

• Local HTTP: set POKER_MODE=local and a random POKER_MCP_TOKEN of at least 32 characters, then run uvicorn poker_spot.http_server:app --host 127.0.0.1 --port 8000 --workers 1. Send bearer auth and appropriate MCP content-type headers. Never use local-token mode on Render.

• Hosted: dedicated Free Render service and Auth0 Free, validating JWT signature, issuer, exact /mcp audience, expiry, poker:solve and approved subject. No unauthenticated solver calls. /health means liveness, /ready verifies configuration, /.well-known/oauth-protected-resource advertises OAuth, and /mcp runs the authorized Streamable HTTP tools.

One hosted worker at a time, 30 calculation starts/minute, 16 KiB request body, 20s wall/process time and Linux CPU/384 MiB address-space limits. Production river CFR permits at most 1,500 iterations, 180 combos per side and 22,500 pairs. The separate, narrower turn pilot has its own contract; do not conflate these limits. Free service cold starts may exceed connector timeouts; no paid plan is authorized.

See hosting and release, CI/deployment operations, and friends-only onboarding design for current instructions. A custom connector or approved account requires actual OAuth completion and a computed tool result before claiming ChatGPT/Claude acceptance. There is no runtime dependency on the trip-planning-engine project.

Read results correctly

• solve_river action EVs use the half-starting-pot baseline. Compare actions at the same node; checking is endogenous. Reach can be zero, in which case an action EV is null; don't interpret rare-node frequencies as precise predictions.

• evaluate_river_call uses pot before the bet: EV versus folding = equity * (pot + 2 * bet) - bet; required equity = bet / (pot + 2 * bet). It does not infer the opponent's betting range or solve equilibrium.

• Low NashConv measures exploitability inside the stated game only. £505 acceptance scenario uses explicitly hypothetical weighted arrivals, not an observed range. See benchmark evidence and limits.

This is a public MIT-licensed repository. Keep credentials and private hand/account data out of commits and artifacts; use post-session analysis only.