Wind MCP

A Model Context Protocol server that gives AI assistants direct access to Wind Financial Terminal data.

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Wind MCP bridges the Wind Financial Terminal (万得) with AI assistants via the Model Context Protocol. It exposes 23 tools + 1 resource covering market data, fundamentals, macro economics, screening, estimates, portfolio management, and date utilities — all accessible through natural language.

Platform: Windows only (WindPy is a Windows COM-based library).

Companion project to Bloomberg-MCP. Same architecture, same philosophy — but for Wind (万得).

You: "拉一下贵州茅台过去20天的量价数据"

Claude: runs wind_historical with codes=600519.SH, fields=close,volume
        → Returns structured price/volume time series

You: "Find me A-share stocks with PE < 15 and ROE > 20%"

Claude: runs wind_dynamic_screen with universe=A-shares, filters, rank
        → Returns filtered and ranked stock list

Architecture

graph TB
    subgraph Clients
        CC[Claude Code]
        WC[Web Client]
        CA[Custom App]
    end

    subgraph "Wind MCP Server"
        direction TB
        MCP["FastMCP Server<br/><i>23 tools + 1 resource</i>"]

        subgraph Handlers["Handler Layer"]
            direction LR
            SNAP[Snapshot & Historical]
            INTRA[Minute Bars & Ticks]
            MACRO[Macro & Sector]
            SCREEN[Screening]
            EST[Estimates & Holders]
            CAL[Calendar & Dates]
        end

        subgraph Core["Core Layer"]
            direction LR
            SESSION["WindSession<br/><i>Singleton + atexit</i>"]
            CACHE["WindCache<br/><i>TTL-based</i>"]
            PARSER["Parser<br/><i>12 parsers</i>"]
            CONV["Converter<br/><i>BBG → Wind</i>"]
        end
    end

    WIND["Wind Terminal<br/><i>WindPy (w.start)</i>"]

    CC -- stdio --> MCP
    WC -- HTTP/SSE --> MCP
    CA -- HTTP/SSE --> MCP
    MCP --> Handlers
    Handlers --> Core
    SESSION <--> WIND

    style MCP fill:#1a73e8,stroke:#1557b0,color:#fff
    style WIND fill:#e65100,stroke:#bf360c,color:#fff
    style SESSION fill:#2e7d32,stroke:#1b5e20,color:#fff
    style CACHE fill:#2e7d32,stroke:#1b5e20,color:#fff

Tools Overview (23 tools + 1 resource)

graph LR
    subgraph "Market Data (5)"
        T1["wind_snapshot<br/><i>WSS current data</i>"]
        T2["wind_historical<br/><i>WSD time series</i>"]
        T3["wind_minute_bars<br/><i>WSI candles</i>"]
        T4["wind_ticks<br/><i>WST raw ticks</i>"]
        T5["wind_realtime<br/><i>WSQ live quotes</i>"]
    end

    subgraph "Fundamentals & Screening (5)"
        T6["wind_dataset<br/><i>WSET tables</i>"]
        T7["wind_screen<br/><i>WEQS screens</i>"]
        T8["wind_dynamic_screen<br/><i>Custom filter + rank</i>"]
        T9["wind_estimates<br/><i>Consensus</i>"]
        T10["wind_holders<br/><i>Shareholding</i>"]
    end

    subgraph "Macro & Sector (3)"
        T11["wind_macro<br/><i>EDB series</i>"]
        T12["wind_sector_series<br/><i>WSES time series</i>"]
        T13["wind_sector_snapshot<br/><i>WSEE snapshot</i>"]
    end

    subgraph "Connect & Calendar (2)"
        T14["wind_stock_connect<br/><i>Northbound flows</i>"]
        T15["wind_event_calendar<br/><i>IPO, earnings...</i>"]
    end

    subgraph "Composite & Portfolio (4)"
        T16["wind_company_profile<br/><i>One-stop overview</i>"]
        T17["wind_portfolio_report<br/><i>WPF reports</i>"]
        T18["wind_portfolio_snapshot<br/><i>WPS holdings</i>"]
        T19["wind_portfolio_series<br/><i>WPD time series</i>"]
    end

    subgraph "Date Utilities (3)"
        T20["wind_trading_days<br/><i>TDAYS</i>"]
        T21["wind_date_offset<br/><i>TDAYSOFFSET</i>"]
        T22["wind_days_count<br/><i>TDAYSCOUNT</i>"]
    end

    subgraph "Observability (1 tool + 1 resource)"
        T23["wind_metrics<br/><i>Server stats</i>"]
        R1["wind://health<br/><i>Health check</i>"]
    end

    style T6 fill:#1a73e8,stroke:#1557b0,color:#fff
    style T7 fill:#1a73e8,stroke:#1557b0,color:#fff
    style T8 fill:#1a73e8,stroke:#1557b0,color:#fff
    style T11 fill:#7b1fa2,stroke:#6a1b9a,color:#fff
    style T12 fill:#7b1fa2,stroke:#6a1b9a,color:#fff
    style T13 fill:#7b1fa2,stroke:#6a1b9a,color:#fff
    style T16 fill:#00695c,stroke:#004d40,color:#fff
    style T17 fill:#00695c,stroke:#004d40,color:#fff
    style T18 fill:#00695c,stroke:#004d40,color:#fff
    style T19 fill:#00695c,stroke:#004d40,color:#fff
    style R1 fill:#546e7a,stroke:#37474f,color:#fff

Key Features

• Bloomberg → Wind Ticker Converter — Accepts Bloomberg-style identifiers (AAPL US Equity, 700 HK Equity, 601012 CH Equity) and auto-converts to Wind codes (AAPL.O, 00700.HK, 601012.SH). Covers US, HK, JP, LN, CH equities, indices, commodities, and currencies.
• Modular architecture — server.py is a thin entry point. Handlers, models, formatters, parsers, and converters cleanly separated.
• 16 FieldSet shortcuts — Pre-defined field collections (PRICE, VALUATION, PROFITABILITY, etc.) that expand to Wind field mnemonics.
• Cache layer — TTL-based in-memory cache with data-type-aware expiration (30s for realtime, 24h for static).
• 12 WindPy parsers — Handle WSS, WSD, WSI, WST, WSQ, WSET, EDB, WSES, WSEE, TDAYS, TDAYSOFFSET, TDAYSCOUNT with NaN→None cleanup and column-to-row transposition.
• Dynamic Screening — Custom filtering with operators (gt, lt, between, in, eq) + ranking + slicing, without knowing Wind mnemonics.

Data Flow

sequenceDiagram
    participant Client as AI Assistant
    participant MCP as MCP Server
    participant Conv as Ticker Converter
    participant Expand as Field Expander
    participant Cache as Cache Layer
    participant Session as WindSession
    participant Wind as Wind Terminal

    Client->>MCP: Tool call (JSON)
    MCP->>Conv: Convert BBG → Wind codes
    Conv-->>MCP: Wind codes

    alt FieldSet shortcuts used
        MCP->>Expand: Expand FieldSet shortcuts
        Expand-->>MCP: Resolved field list
    end

    MCP->>Cache: Check cache
    alt Cache hit
        Cache-->>MCP: Cached result
    else Cache miss
        MCP->>Session: Call WindPy API
        Session->>Wind: w.wsd() / w.wss() / ...
        Wind-->>Session: WindData response
        Session-->>MCP: Parsed dicts
        MCP->>Cache: Store with TTL
    end

    alt Markdown format
        MCP-->>Client: Formatted table
    else JSON format
        MCP-->>Client: Structured JSON
    end

Tool Reference

Market Data

Tool	WindPy API	Description	Key Parameters
wind_snapshot	WSS	Current field values for any security	codes, fields, trade_date
wind_historical	WSD	Time series with configurable periodicity	codes, fields, begin_date, end_date
wind_minute_bars	WSI	OHLCV intraday candles (1/3/5/15/30/60 min)	codes, fields, begin_time, end_time, bar_size
wind_ticks	WST	Raw tick-level trade data	codes, fields, begin_time, end_time
wind_realtime	WSQ	Live streaming quotes	codes, fields

Fundamentals & Screening

Tool	WindPy API	Description	Key Parameters
wind_dataset	WSET	Structured datasets (index members, IPOs, etc.)	table_name, options
wind_screen	WEQS	Execute saved Wind stock screens	screen_name, options
wind_dynamic_screen	WSS	Custom filter + rank + slice	universe, fields, filters, rank_by, top_n
wind_estimates	WSS	Consensus estimates and target prices	codes, metrics, year
wind_holders	WSS/WSET	Top holders, institutional, fund holdings	codes, holder_type, date

Macro & Sector

Tool	WindPy API	Description	Key Parameters
wind_macro	EDB	Macroeconomic indicator time series	codes, begin_date, end_date
wind_sector_series	WSES	Sector-level time series	codes, fields, begin_date, end_date
wind_sector_snapshot	WSEE	Sector-level current snapshot	codes, fields, trade_date

Stock Connect & Calendar

Tool	WindPy API	Description	Key Parameters
wind_stock_connect	WSET/WSS	Northbound/Southbound flow data	codes, direction, date
wind_event_calendar	WSET	IPO, earnings, dividend calendars	event_type, begin_date, end_date

Composite & Portfolio

Tool	WindPy API	Description	Key Parameters
wind_company_profile	WSS+WSD	One-stop company overview (snapshot + estimates + price history)	codes
wind_portfolio_report	WPF	Portfolio performance/attribution/risk reports	product_name, table_name, options
wind_portfolio_snapshot	WPS	Portfolio NAV, holdings, weights, PnL	portfolio_name, fields, options
wind_portfolio_series	WPD	Portfolio performance time series	portfolio_name, fields, begin_date

Observability

Tool	Type	Description
wind_metrics	Tool	Server metrics: tool call counts, latency, cache hit rate, uptime
wind://health	Resource	Wind connection and cache health status

Date Utilities

Tool	WindPy API	Description	Key Parameters
wind_trading_days	TDAYS	List trading days in a range	begin_date, end_date, calendar
wind_date_offset	TDAYSOFFSET	Offset a date by N trading days	date, offset, calendar
wind_days_count	TDAYSCOUNT	Count trading days between two dates	begin_date, end_date, calendar

All tools support response_format: "markdown" (default) or "json".

FieldSet Shortcuts

Instead of remembering Wind field mnemonics, use shorthand names that expand to multiple fields.

FieldSet	Fields	Key Wind Mnemonics
PRICE	5	close, open, high, low, pct_chg
MOMENTUM	4	pct_chg, pct_chg_5d, pct_chg_1m, pct_chg_ytd
VOLUME_PROFILE	4	volume, amt, turn, free_turn
VALUATION	5	pe_ttm, pb_lf, ps_ttm, pcf_ocf_ttm, ev2_to_ebitda
VALUATION_EXTENDED	9	+ pe_est, dividend_yield, total_mkt_cap, ev
PROFITABILITY	6	roe_ttm, roa_ttm, grossprofitmargin, netprofitmargin, operatingprofitmargin, roic
GROWTH	4	yoyprofit, yoyrevenue, yoyocf, qfa_yoygr
BALANCE_SHEET	6	debttoassets, current_ratio, quick_ratio, cashflow_to_debt, longdebttodebt, equity_ratio
CASH_FLOW	5	ocfps, fcf, cf_from_ops, capex, dividendps
TECHNICAL	5	rsi, macd, vol_20d, beta_100w, atr_14d
ANALYST	4	rating_avg, est_target_price, est_eps_fy1, est_net_profit_fy1
ESTIMATE_REVISIONS	4	est_eps_chg_4w, est_eps_chg_13w, est_num_up, est_num_down
SECTOR	2	industry_sw, industry_sw_lv2
NORTHBOUND	4	sh_hk_share_pct, sh_hk_share_chg, sh_hk_share_amt, sh_hk_share_rank
MARGIN	3	margin_buy_bal, margin_sell_bal, margin_net_bal
RISK	5	beta_100w, volatility_20d, volatility_60d, sharpe_20d, max_drawdown_1y
SCREENING_FULL	50+	All of the above combined

Bloomberg → Wind Ticker Conversion

Wind MCP automatically converts Bloomberg-style identifiers to Wind codes:

Bloomberg Format	Wind Code	Market
AAPL US Equity	AAPL.O	US (NASDAQ)
JPM US Equity	JPM.N	US (NYSE)
700 HK Equity	00700.HK	Hong Kong
7203 JP Equity	7203.T	Japan
VOD LN Equity	VOD.L	London
601012 CH Equity	601012.SH	A-share (Shanghai)
000001 CH Equity	000001.SZ	A-share (Shenzhen)
300750 CH Equity	300750.SZ	A-share (ChiNext)
SPX Index	SPX.GI	Index
HSI Index	HSI.HI	Index
CL1 Comdty	CL.NYM	Commodity
EURUSD Curncy	EURUSD.FX	Currency
600519.SH	600519.SH	Passthrough (already Wind)

Dynamic Screening

Build custom screens with pre-validated field sets, filters, and ranking — no need to know Wind field mnemonics.

flowchart LR
    A["Universe<br/><i>index, sector,<br/>or ticker list</i>"] --> B["Field Expansion<br/><i>FieldSet shortcuts<br/>→ Wind fields</i>"]
    B --> C["Wind API<br/><i>WSS request</i>"]
    C --> D["Filter<br/><i>gt, lt, between,<br/>in, eq, ...</i>"]
    D --> E["Rank & Slice<br/><i>rank_by + top_n</i>"]
    E --> F["Response<br/><i>Markdown table<br/>or JSON</i>"]

    style A fill:#e8f5e9,stroke:#2e7d32
    style C fill:#fff3e0,stroke:#ff6f00
    style F fill:#e3f2fd,stroke:#1a73e8

Filter Operators

Operator	Description	Example
gt / gte	Greater than (or equal)	{"field": "roe_ttm", "op": "gt", "value": 20}
lt / lte	Less than (or equal)	{"field": "pe_ttm", "op": "lt", "value": 15}
eq / neq	Equals / not equals	{"field": "industry_sw", "op": "eq", "value": "电子"}
between	Range (inclusive)	{"field": "pe_ttm", "op": "between", "value": [10, 25]}
in	Value in list	{"field": "industry_sw", "op": "in", "value": ["电子", "计算机"]}

Example: Find Undervalued High-ROE A-shares

{
  "universe": "sector:全部A股",
  "fields": ["PRICE", "VALUATION", "PROFITABILITY"],
  "filters": [
    {"field": "pe_ttm", "op": "lt", "value": 15},
    {"field": "roe_ttm", "op": "gt", "value": 20}
  ],
  "rank_by": "roe_ttm",
  "rank_descending": true,
  "top_n": 20
}

Cache Layer

Built-in cache reduces Wind API load with data-type-aware TTLs:

Data Type	Default TTL	Rationale
Realtime quotes (WSQ)	30 seconds	Near real-time
Snapshot (WSS)	5 minutes	Moderate refresh
Minute bars (WSI)	5 minutes	Intraday refresh
Ticks (WST)	1 minute	High-frequency
Portfolio (WPF/WPS/WPD)	5 minutes	Moderate refresh
Screening (WEQS)	10 minutes	Moderate refresh
Estimates	4 hours	Consensus updates infrequently
Historical (WSD)	12 hours	End-of-day data stable
Macro data (EDB)	24 hours	Periodic updates
Dataset (WSET)	24 hours	Reference data
Sector (WSES/WSEE)	24 hours	Rarely changes
Holders / Dates	24 hours	Rarely changes

All TTLs are configurable via wind_mcp.toml or environment variables. See Configuration.

Configuration

Server behavior can be customized via wind_mcp.toml in the project root. All values can also be overridden via environment variables with the prefix WIND_MCP_ (e.g., WIND_MCP_CACHE_MAXSIZE=5000).

[session]
connect_timeout = 30        # Seconds to wait for Wind connection
reconnect_retries = 3       # Auto-reconnect attempts
reconnect_backoff = 1.0     # Backoff multiplier between retries

[cache]
maxsize = 2000              # Max cached entries (LRU eviction)
ttl_realtime = 30           # WSQ — near real-time
ttl_snapshot = 300          # WSS — 5 min
ttl_historical = 43200     # WSD — 12 hours
ttl_dataset = 86400        # WSET — 24 hours
ttl_macro = 86400          # EDB — 24 hours
ttl_portfolio = 300        # WPF/WPS/WPD — 5 min

[api]
timeout = 30.0              # Per-call timeout (seconds)
retries = 2                 # Retry count on transient errors
backoff = 1.0               # Backoff multiplier

[log]
format = "text"             # "json" or "text"
level = "INFO"

Project Structure

wind-mcp/
├── pyproject.toml
├── README.md
├── LICENSE
├── wind_mcp.toml                  # Server configuration (cache TTL, timeouts, retries)
├── run_server.bat / run_server.ps1
├── src/wind_mcp/
│   ├── __init__.py
│   ├── __main__.py
│   ├── server.py                  # FastMCP entry point, 23 tools + 1 resource
│   ├── formatters.py              # Markdown table & JSON output
│   ├── core/
│   │   ├── session.py             # WindSession singleton + reconnect
│   │   ├── cache.py               # TTL cache with LRU eviction
│   │   ├── parser.py              # 12 WindData parsers
│   │   ├── converter.py           # Bloomberg → Wind ticker converter
│   │   ├── executor.py            # Single-thread executor for Wind API calls
│   │   ├── validators.py          # Input validation (codes, dates, fields)
│   │   ├── resilience.py          # Timeout, retry, stale-cache fallback
│   │   ├── config.py              # Centralized config (env > toml > defaults)
│   │   ├── metrics.py             # Counters + histograms for observability
│   │   ├── universe.py            # Universe resolution (index/sector → security list)
│   │   └── filters.py             # In-memory data filtering (gt/lt/between/in/...)
│   ├── models/
│   │   ├── enums.py               # ResponseFormat, Periodicity, etc.
│   │   └── inputs.py              # Pydantic input models
│   ├── tools/
│   │   ├── fieldsets.py           # 16 FieldSet definitions
│   │   └── field_expander.py      # FieldSet → field list resolver
│   ├── handlers/                  # 16 handler modules
│   │   ├── snapshot.py            # WSS
│   │   ├── historical.py          # WSD
│   │   ├── minute_bars.py         # WSI
│   │   ├── ticks.py               # WST
│   │   ├── realtime.py            # WSQ
│   │   ├── dataset.py             # WSET
│   │   ├── macro.py               # EDB
│   │   ├── sector.py              # WSES / WSEE
│   │   ├── screening.py           # WEQS + dynamic screen
│   │   ├── estimates.py           # Consensus estimates
│   │   ├── holders.py             # Holder analysis
│   │   ├── stock_connect.py       # Northbound/Southbound
│   │   ├── calendar.py            # Event calendar
│   │   ├── dates.py               # TDAYS / TDAYSOFFSET / TDAYSCOUNT
│   │   ├── composite.py           # Company profile (multi-source)
│   │   └── portfolio.py           # WPF / WPS / WPD portfolio tools
│   └── data/                      # Static mapping files
│       ├── us_exchange_map.json   # ~200 US tickers → exchange
│       ├── index_map.json         # BBG → Wind index mapping
│       ├── commodity_map.json     # BBG → Wind commodity mapping
│       └── currency_map.json      # BBG → Wind currency mapping
├── tests/                         # 101 unit tests (no Wind needed)
│   ├── test_parser.py
│   ├── test_fieldsets.py
│   ├── test_cache.py
│   ├── test_config.py
│   ├── test_converter.py
│   ├── test_filters.py
│   ├── test_formatters.py
│   ├── test_inputs.py
│   ├── test_metrics.py
│   ├── test_resilience.py
│   └── test_validators.py
└── examples/
    ├── basic_usage.py
    └── screening_example.py

Installation

Prerequisites

• Windows (WindPy is a Windows COM-based library)
• Python 3.10+ (must match Wind Terminal bitness — typically 64-bit)
• Wind Financial Terminal (万得) running and logged in (iWind or WFT)
• WindPy — installed via Wind Terminal, NOT via pip. Open Wind Terminal → click "Repair" or install the WindPy plugin from the Tools menu.

Verify WindPy

Before installing Wind MCP, verify that WindPy works in your Python environment:

python -c "from WindPy import w; w.start(); print(w.isconnected())"
# Should print: True

If this returns False or errors, fix your WindPy installation first. Common issues:

• Wind Terminal not running / not logged in
• Python bitness mismatch (e.g., 32-bit Python with 64-bit Wind)
• WindPy not installed (repair via Wind Terminal)

Install

# From source
git clone https://github.com/QmQsun/Wind-MCP.git
cd Wind-MCP
pip install .            # standard install
# or: pip install -e .   # editable mode (for development)

# Or from PyPI
pip install wind-mcp

Configure Claude Code

Add a .mcp.json file to register the MCP server. Two options:

Global (all projects can use Wind MCP) — place at ~/.mcp.json (i.e., C:\Users\<you>\.mcp.json):

{
  "mcpServers": {
    "wind-mcp": {
      "command": "wind-mcp",
      "args": []
    }
  }
}

Project-level (only one project) — place .mcp.json in the project root directory.

The wind-mcp command is the console entry point installed by pip. Alternatively, use "command": "python", "args": ["-m", "wind_mcp.server"].

Quick Start

As an MCP Server

# stdio (default — for Claude Code)
python -m wind_mcp.server

# HTTP transport (for web clients)
python -m wind_mcp.server --http --port=8080

# SSE transport (for streaming clients)
python -m wind_mcp.server --sse --port=8080

Windows

# Command Prompt
run_server.bat

# PowerShell
.\run_server.ps1

Wind API Coverage

graph LR
    subgraph "Wind Terminal (WindPy)"
        WSS["WSS<br/><i>Snapshot</i>"]
        WSD["WSD<br/><i>Historical</i>"]
        WSI["WSI<br/><i>Minute bars</i>"]
        WST["WST<br/><i>Tick data</i>"]
        WSQ["WSQ<br/><i>Realtime</i>"]
        WSET["WSET<br/><i>Datasets</i>"]
        EDB["EDB<br/><i>Macro</i>"]
        WSES["WSES<br/><i>Sector series</i>"]
        WSEE["WSEE<br/><i>Sector snapshot</i>"]
        WEQS["WEQS<br/><i>Stock screener</i>"]
        TDAYS["TDAYS<br/><i>Trading days</i>"]
    end

    WSS --- T1[Snapshot + Estimates + Holders + Screen]
    WSD --- T2[Historical Time Series]
    WSI --- T3[Intraday Bars]
    WST --- T4[Tick Data]
    WSQ --- T5[Realtime Quotes]
    WSET --- T6[Datasets + Connect + Calendar]
    EDB --- T7[Macro Indicators]
    WSES --- T8[Sector Time Series]
    WSEE --- T9[Sector Snapshot]
    WEQS --- T10[Saved Screens]
    TDAYS --- T11[Date Utilities]

    style WSS fill:#1a73e8,stroke:#1557b0,color:#fff
    style WSD fill:#1a73e8,stroke:#1557b0,color:#fff
    style EDB fill:#7b1fa2,stroke:#6a1b9a,color:#fff
    style WEQS fill:#e65100,stroke:#bf360c,color:#fff

Contributing

Contributions welcome! Please open an issue or submit a pull request.

pip install -e ".[dev]"
pytest                    # Unit tests (no Wind Terminal needed)
black src/ tests/
ruff check src/ tests/

Related Projects

• Bloomberg-MCP — Same architecture for Bloomberg Terminal

License

MIT — see LICENSE for details.