Backtest360

com.backtest360/backtest360 · v0.5.0

MCP server exposing the Backtest360 engine API as tools for AI agents.

MCPremotelocal · pypiAPI keyFinanceDocuments & PDF

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Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 20 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

B 75/100

What it does: 20 tools · 16 read, 1 write · Finance, Documents & PDF

Test call list_indicators: needs a key: HTTP 401 (1,022 ms)

How the rating is made

Answers without login: +30
Speed of first answer: +10
Lists tools: +10
Tool descriptions: +15
Parameter descriptions: +2
Read/write annotations: 0
Safe test call: +8
More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL

https://mcp.backtest360.com/mcp

Package

registry:   pypi
identifier: backtest360-mcp
version:    0.5.0
transport:  stdio

Tools

20 tools listed at last check

get_me The configured API key's permissions, limits, and current usage. Cheap. Call early in a session — before planning work — to learn what this key can do instead of discovering limits through failed calls. Returns: ``scopes``: the permission scopes the key carries.
engine_info Engine version, API contract number, and health. Free (not quota-counted). Call once at the start of a session to confirm the engine is reachable and which contract it serves.
get_catalog Fetch one engine reference catalog. Catalogs (cheap, cacheable per session): - 'operators' — comparison operators for condition expressions - 'execution-modes' — entry/exit anchors and fill algorithms, with the validity matrix by market type - 'stop-types'
list_indicators List indicators, or fetch one indicator's full schema. Cheap, cacheable per session. With no arguments: a compact catalog — ``{"indicators": [...], "count": N}`` — where each entry carries id, name, category, kind, and value_dtype (no description, to keep the discov
list_templates List predesigned strategy templates, or fetch one in full. Cheap, cacheable per session. The engine returns the templates available to the calling key. With no arguments: a compact catalog — ``{"templates": [...], "count": N}`` — where each entry carries id, origin,
get_strategy_schema JSON Schema for the strategy document (condition_tree + indicators). Fetch this before composing a strategy by hand; the validate_strategy tool checks against the same rules.
validate_strategy Validate a strategy document without running a backtest. A cheap quota separate from backtest runs, so validate freely and ALWAYS before run_backtest. Args: strategy: The strategy document — name, indicators[], and condition_tree (see get_strateg
run_backtest Run a historical backtest against the engine. Quota-counted and compute-bound. Validate the strategy first (validate_strategy is far cheaper). On a 504 compute timeout, do NOT retry the same request — reduce the date range, use a coarser frequency, or simplify the st
get_latest_signal Evaluate the strategy on the most recent bar only — no P&L, no stats. Returns the latest signal (-1/0/1), which condition slots fired, and the bar timestamp. Use for "what would this strategy do right now" questions; use run_backtest for performance.
compare_backtests Run several strategies on the same data and compare side by side. One quota-counted call, but compute scales with the number of strategies. If the wall-clock compute budget is exceeded, the call fails with a tool error (504) instead of returning partial results — nar
export_backtest Export a multi-strategy comparison as an Excel workbook. Quota-counted; needs a key whose plan includes full-metrics export (a 403 means the configured key's plan does not — do not retry). Returns the workbook base64-encoded — decode and write it to a ``.xlsx`` file.
compute_stats Compute the engine's performance metrics from a returns series. Use when the returns came from somewhere other than run_backtest (an external system, a portfolio) — backtest results already include these statistics. Args: returns: Per-bar log returns as
search_tickers Search available assets by ticker or name (relevance-ranked). Use to resolve a user's asset mention ("bitcoin", "S&P") to the exact ticker before requesting a server-side data fetch. asset_class filters to 'stocks', 'crypto', 'forex', or 'indices'.
list_tickers List available tickers, optionally filtered by asset class. The full universe is very large, so the MCP server caps the returned list and marks it ``truncated_by_mcp`` — pass asset_class to narrow it, or use search_tickers to resolve a specific asset by name.
get_data_range Available date range and estimated bar count for a symbol/frequency. Available on paid plans. Call before a server-side fetch so the requested start/end stay inside what the provider can deliver and the bar count stays inside the key's per-run limit.
get_ticker_info Identity and data coverage for one symbol, in a single call. Metadata only — no market data, so no paid plan is needed. Returns the asset's identity (name, asset class, exchange, currency, and whether it is still active) together with a coverage summary for the given
get_quote Latest available price for a symbol. Requires a paid plan (managed market data). Returns the most recent *available* bar for the given frequency — the end-of-day close for daily, the last completed bar otherwise — as open/high/low/close/volume plus an ``as_of`` times
get_price_history OHLCV price history for a symbol over a date range. Requires a paid plan (managed market data). ``start`` is required (``YYYY-MM-DD``); ``end`` defaults to today. Returns a summary (symbol, resolved date range, total bar count, price range, gap flags), market-hours d
list_macro_series List the available macroeconomic series (the catalog). Free — no special plan. Returns the set of macro series you can fetch with get_macro_series, each with its stable ``id`` (the value get_macro_series takes), title, category, native reporting frequency, and units,
get_macro_series Observations for one macroeconomic series over an optional date range. Free — no special plan. ``series`` is an ``id`` from list_macro_series (e.g. treasury_10y, cpi, unemployment_rate); arbitrary external ids are not accepted. ``start``/``end`` are ``YYYY-MM-DD``, inclusive

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