QuantWright MCP server

• Registry namecom.quantwright/agent-apiverified in the MCP registry

The registry name sits under quantwright.com. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.

• Stateanswerschecked 2026-10-30
• Tools6
• Server calls itselfquantwright
• Server version1.0.0
• Protocol version2025-06-18

On 2026-10-30 the server answered initialize and tools/list without a sign-in. First answer in 269 ms.

• Its tools do every use case we checked: backtest a strategy with trading costs included; check whether a backtest holds across different time periods.
• Checked on 4 of the 7 days it takes to judge reliability.

Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.

• INITE MCP scoreafter a weeka score needs 7 daily checks: 4 so far
• What an agent can do with it2 of 2 use cases
• Answeredmeasuring4 of the 7 daily checks it takes to print a share
• Median first answer1686 ms
• Space in an agent's context≈ 2,528 tokensthe definitions of all its tools (6), which an agent carries on every turn
• Tool definitionsA · 92 of 100
• Typed results6 of 6 toolsdeclared outputSchema: results come typed, read once

• Parameters without a description: in 3 of 6

A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (25%), doing the product's job (25%), definitions (20%), context (10%), use (10%) and how readily a client connects (10%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →

• describe_data

  Start here to backtest a trading idea. This server holds the price history (US stocks and ETFs, spot crypto, FX, spot gold and silver; daily and intraday bars) and runs backtests on it, so no price data needs to be downloaded or found on…

• create_study

  Opens a study, the named set of runs every backtest belongs to: call it once per question, before run_backtest. Can set a hold-out period, once and only here, that no run tests except run_held_out_test. Only the first held-out test per…

• run_backtest

  Backtests a trading rule on this server's price history: one backtesting.py Strategy class, one symbol, one bar size, in a study. Use it to test, backtest or evaluate a trading rule or strategy, instead of downloading prices or searching…

• get_result

  Reads a backtest result by its run_id (when run_backtest answered "running", call this until the run ends), or a study's runs by study_id (one of them with version). A run comes with its trades, a page at a time (trades_page).

• run_held_out_test

  The final out-of-sample check: runs a finished run's exact code once over its study's hold-out period. Call it at the end, on the run you would keep: the first held-out test per account and market is the one that counts, and a hold-out…

• compare_trades

  Checks a trader's own trades against a run's rule, on the price history this server holds: for each trade, in their order, whether the rule would have taken it and, if not, why (already in a trade, no entry signal that day, no bar that…