Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
MCP server exposing the Backtest360 engine API as tools for AI agents.
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Pick the AI app you use, then copy the settings.
BACKTEST360_API_KEY, X-API-KeyValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"backtest360": {
"command": "uvx",
"args": [
"backtest360-mcp"
],
"env": {
"BACKTEST360_API_KEY": "your-value"
}
}
}
}Run this in your terminal
claude mcp add --transport http backtest360 https://mcp.backtest360.com/mcp --header 'X-API-Key: your-value'claude mcp add backtest360 --env BACKTEST360_API_KEY=your-value -- uvx backtest360-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"backtest360": {
"url": "https://mcp.backtest360.com/mcp",
"headers": {
"X-API-Key": "your-value"
}
}
}
}Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"backtest360": {
"command": "uvx",
"args": [
"backtest360-mcp"
],
"env": {
"BACKTEST360_API_KEY": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"backtest360": {
"type": "http",
"url": "https://mcp.backtest360.com/mcp",
"headers": {
"X-API-Key": "your-value"
}
}
}
}Paste into .vscode/mcp.json in your project
{
"servers": {
"backtest360": {
"type": "stdio",
"command": "uvx",
"args": [
"backtest360-mcp"
],
"env": {
"BACKTEST360_API_KEY": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.
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X-API-Key secret required HTTP headerThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Tool names and descriptions exactly as the server reported them on Nov 10, 2026. The maker wrote them, not us; we show them as plain text.
get_meThe 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. ``limits``: reque
engine_infoEngine 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_catalogFetch 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' — stop-loss types, re-e
list_indicatorsList 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 discovery scan small
list_templatesList 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, name, and des
get_strategy_schemaJSON 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_strategyValidate 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_strategy_schema for the exact shape). inj
run_backtestRun 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 strategy. On 42
get_latest_signalEvaluate 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_backtestsRun 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 — narrow the reque
export_backtestExport 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. Args: data_s
compute_statsCompute 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 {"dates": [...], "values":
search_tickersSearch 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_tickersList 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_rangeAvailable 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_infoIdentity 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 frequency: t
get_quoteLatest 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`` timestamp for that
get_price_historyOHLCV 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 detection, and
list_macro_seriesList 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, plus the lis
get_macro_seriesObservations 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, bot
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 10, 2026
The registry name was verified against the domain backtest360.com (the registry checks domain ownership)
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Read 20 tool descriptions and found no hidden instructions to the AI
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: BACKTEST360_API_KEY, X-API-Key
Either way works: install it on your computer or connect to the cloud version.
The GitHub repo last changed –, and the latest version (0.5.0) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Spec Driven Development, Remote Desktop Commander, Screencast MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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MCP server exposing the Backtest360 engine API as tools for AI agents.
Connect any MCP-capable AI client and drive real backtests conversationally: discover indicators, build and validate strategies, run backtests, and read the results — all against the deterministic Backtest360 engine. The server contains no AI and computes no numbers of its own; it is a thin, faithful adapter over the engine HTTP API. Your engine API key and its plan govern everything (permissions, rate limits, data access).
Two transports: a hosted HTTP endpoint at https://mcp.backtest360.com/mcp (send your key as an X-API-Key header) and local stdio (self-host — see below).
pip install backtest360-mcp # or, from a clone: pip install -e .
Requires Python 3.10+ and a Backtest360 API key. Get one free, instantly at backtest360.com/api-access — submit your email and a key (format b360_…) is issued on the spot and emailed to you; no approval needed. Authentication is API-key only. The free tier runs backtests on data you upload; fetching historical price data from the engine server-side is a paid capability.
Everything is environment-driven:
| Variable | Required | Default | Purpose |
|---|---|---|---|
BACKTEST360_API_KEY | yes | — | Engine API key, sent as X-API-Key |
BACKTEST360_ENGINE_URL | no | https://api.backtest360.com | Engine base URL |
BACKTEST360_MCP_TIMEOUT | no | 300 | Per-request timeout (seconds) |
BACKTEST360_MCP_MAX_OUTPUT_BYTES | no | 100000 | Hard cap on a single tool result |
Point your MCP client at the hosted endpoint over HTTP and send your key as an X-API-Key header:
{
"mcpServers": { "backtest360": { "type": "streamable-http", "url": "https://mcp.backtest360.com/mcp", "headers": { "X-API-Key": "b360_..." } } } }
Run the server yourself and let your client launch it over stdio (the common mcpServers shape):
{
"mcpServers": { "backtest360": { "command": "backtest360-mcp", "env": { "BACKTEST360_API_KEY": "b360_..." } } } }
Prefer not to put the key in a config file? Point command at a small wrapper script that exports the key from your secrets manager and then runs backtest360-mcp. A minimal example config is in examples/mcp.json.
| Tool | What it does |
|---|---|
engine_info | Engine version, API contract, health |
get_me | What the configured key can do: permission scopes, limits, current usage, capability flags |
get_catalog | Reference catalogs: operators, execution modes, stop types, sizing methods, bar frequencies, metric sections |
list_indicators | Indicator discovery; per-indicator parameter schemas |
list_templates | Predesigned strategy templates — discover compactly, fetch one in full, ready to validate and run |
get_strategy_schema | JSON Schema for strategy documents |
validate_strategy | Validate a strategy without running it — returns structured, locatable errors |
run_backtest | Run a historical backtest |
get_latest_signal | Evaluate the most recent bar only (no P&L) |
compare_backtests | Run several strategies on the same data, side by side |
compute_stats | Compute the metric set from an externally produced returns series |
search_tickers / list_tickers | Asset discovery for server-side data fetch |
get_data_range | Available history and bar-count estimate for a symbol |
get_ticker_info | Symbol identity and data coverage in a single call |
get_quote | Latest available price for a symbol (paid plan) |
get_price_history | OHLCV price history over a date range (paid plan; long histories downsampled to fit) |
list_macro_series / get_macro_series | Macroeconomic data: list the series catalog, then fetch one series' observations |
The cheap static catalogs are also published as MCP resources (backtest360://catalog/{name}, backtest360://schema/strategy) for clients that support resource attachment.
Two workflow prompts scaffold the common multi-tool flows for a connected AI: each names which tools to call, in what order, and what to look at in the results. They carry no interpretation and compute nothing — the connected AI does the reasoning.
| Prompt | Arguments | What it scaffolds |
|---|---|---|
robustness_review | symbol, strategy (optional) | Review a backtested strategy for robustness: validate → run → compare against buy-and-hold → weigh the evidence base (sample size, significance/robustness statistics, warnings) → caveated summary |
build_and_validate | idea | Turn a plain-language idea into a validated strategy: survey the catalogs → fetch the schema → construct → validate-and-fix loop → dry-run |
A full backtest result is megabytes; an agent's context is not. run_backtest and compare_backtests take response_detail:
summary (default) — headline metrics, warnings, counts, equity endpointsstats — every metric the plan allowsfull — plus series (downsampled, endpoints preserved) and trades (paginated)run_backtest also takes max_series_points (default 500, must be >= 2) to override the series downsampling cap — set it higher for full-resolution series on a long run, or leave it unset for today's default.
include=["trades", "equity_curve", "monthly_returns", "yearly_returns", "signal_diagnostics"] adds specific blocks at any detail level. signal_diagnostics reports which per-bar entry/exit conditions fired, as a capped list of fire dates per condition (not the raw per-bar boolean arrays, which downsampling would corrupt) — or {"available": false, ...} when the run has no condition tree to evaluate (e.g. precomputed signals). Results exceeding the output cap are reduced further and explicitly marked truncated_by_mcp — never silently cut. Shaping only ever selects and thins what the engine returned; no value is computed or altered.
Designed for agents:
{"valid": false, "errors": [...]} with machine codes and document locations; engine rejections arrive as {"accepted": false, "error": ...} with a hint.Retry-After value; engine-busy says retry with backoff; a compute timeout says do not retry and reduce scope instead; permission problems name the missing capability. Engine request ids are included for support.pip install -e ".[dev]"
pytest # unit suite vs a mock engine — no network
Questions or feedback? hello@backtest360.com — we read everything. backtest360-mcp is in active development, so help shape it.
Bug reports and feature requests: open an issue on GitHub.
MIT — see LICENSE.