The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Tally MCP listing page.
Every trading connector makes your AI more capable. Tally makes it accountable.
Tally (tally.markets) is a trading-discipline layer that mounts inside Claude, ChatGPT, Claude Code, and any MCP-capable agent. Your AI is the analyst — it researches, monitors, and gathers evidence. Tally holds the record neither you nor the model can rewrite: pre-registered theses, exit rules that freeze before capital moves, a 24-hour cooling-off, an override ledger for rule-breaking exits, and a public receipt for every closed trade.
Tally never executes trades. Every broker and venue connection is read-only at the API level — no order placement, no custody, by architecture and by policy.
Server URL (Streamable HTTP · OAuth 2.0 with dynamic client registration):
| Client | How |
|---|---|
| Claude | Settings → Connectors → Add custom connector → name it Tally, paste the URL. Leave the OAuth fields empty — Tally registers itself. |
| ChatGPT | Listed app — one click from the directory, no developer mode. (Manual fallback: developer mode → Plugins → New plugin, the URL as Server URL, OAuth.) |
| Claude Code | claude mcp add --transport http tally https://tally.markets/api/mcp, then /mcp to sign in. |
| Any MCP agent | Point it at the URL above; OAuth discovery does the rest. |
Then say: "Get started with Tally, then run my checkup." The server teaches your AI the whole protocol on first contact.
Full walkthrough (skill, scheduled morning checkup, broker linking): tally.markets/connect
| Tool | What it does |
|---|---|
get_started | Returns the discipline protocol — the AI teaches itself |
get_checkup | Morning briefing: active theses, deadlines, evidence, closed history and lifetime R |
list_theses / get_thesis | Read the journal |
create_thesis | Pre-register a trade: statement, mechanism, risk budget, exit criteria (starts the 24h cooling-off) |
arm_thesis | Freeze the criteria after cooling-off — from here they fire, never edit |
record_reading | Log evidence against a criterion (the generic sensor primitive) |
fire_criterion | Mark a rule objectively triggered, with cited evidence — one-way |
close_thesis | Close a trade; discretionary closes require a written justification, logged forever |
get_receipt_link | The public receipt for a closed thesis |
Reads are safe to always-allow; writes are guarded by the protocol itself (cooling-off, criteria minimums, override justifications).
Clients with a prompt picker get the three jobs Tally exists for, ready to run:
| Prompt | What it does |
|---|---|
morning-checkup | The daily run — what needs action, fresh readings against every active thesis's criteria, anything that fired. This is the one to put on a schedule. |
pre-register-trade | Turns an idea into a pre-registered thesis, interviewing you until it is falsifiable |
close-out | Walks a thesis to its exit — what the written rules demand, and the justification the override ledger requires if you are closing early |
A real receipt — pre-registered thesis, venue-verified entry and exit, −0.22R, graded Process B / Outcome D, closing note verbatim: "Wrong on thesis, right on process."
Market-data connectors inform your AI. Execution connectors let it trade. Journal connectors show it your past. Tally is the one built to constrain — it runs alongside all of them: tally.markets/compare
Tally is a hosted service. This repository is its documentation and public manifest, not its source — there is nothing here to install or run. Point your AI at the connector URL above; OAuth does the rest.