tally

Tally — the risk officer for AI-assisted trading

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.

Connect

Server URL (Streamable HTTP · OAuth 2.0 with dynamic client registration):

https://tally.markets/api/mcp

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

Tools

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).

Prompts

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

Proof

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."

How it compares

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

Privacy & security

• OAuth per user; your AI sees your journal only, under a grant you can revoke any time.
• Brokerage data (via SnapTrade) is read-only; broker credentials never touch Tally.
• Details: privacy · terms · support@tally.markets

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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.