AKShare One MCP Server

Quick Verdict

AKShare One MCP Server is a practical open-source bridge between MCP clients and public Chinese stock-market data. It exposes nine tools for historical prices, real-time quotes, stock news, three financial statements, financial metrics, insider transactions, and trading-day information. The current PyPI release is 0.3.9, requires Python 3.12 or newer, uses the MIT license, and can run over local stdio or Streamable HTTP.

Use it for research prototypes, education, and personal market review, not automated trading. Its convenience does not turn public web data into an exchange-grade feed. Results depend on upstream sources such as Eastmoney, Sina, and Xueqiu, whose fields, latency, availability, and usage rules can change independently. The server has no built-in enterprise authentication or investment-suitability controls. A safe workflow uses the model to retrieve and organize evidence, then verifies important numbers against an independent source.

Best For

• MCP developers testing how an agent retrieves structured Chinese market data before producing analysis.
• Quant learners who want to request a small dataset conversationally and continue in a controlled Python workflow.
• Finance educators demonstrating data provenance, adjustment methods, indicators, and model limitations.
• Individual researchers drafting company reviews or event studies without placing trades.
• Not ideal for institutions requiring licensed redistribution, exchange-level latency, audited entitlements, an SLA, or order execution.

Key Features

• Historical prices: get_hist_data supports date ranges, several intervals, forward or backward adjustment, recent-row limits, and technical indicators.
• Real-time quotes: get_realtime_data can select supported public sources, although “real time” remains subject to upstream delay and market hours.
• News retrieval: get_news_data provides company-related articles for event timelines. Treat all returned prose as untrusted external input.
• Financial statements: separate balance-sheet, income-statement, and cash-flow tools make period comparisons easier to structure.
• Metrics and insider transactions: useful for screening and review, but neither tool creates a validated investment signal.
• Two transports: stdio fits a single local client; Streamable HTTP can serve a controlled remote environment.
• Model independence: any compatible MCP client can call the tools. Parameter selection and analytical quality still depend on the chosen model and prompt.

Use Cases

• Build a company fact sheet by fetching recent statements and creating a checklist of changes that a person verifies.
• Align company news dates with historical prices to prepare, rather than prove, an event-study hypothesis.
• Teach MA, MACD, RSI, BOLL, adjustment choices, and the difference between an indicator and a decision rule.
• Run fixed-symbol regression checks that detect missing columns or changed source behavior after dependency updates.
• Prototype locally over stdio before deciding whether the workload justifies a protected HTTP deployment.

The tool should remain a retrieval component. Calculations need reproducible code, conclusions need human review, and any trade decision needs a regulated process outside the MCP server.

Pricing

The repository and PyPI package are free. MIT covers the project code, but it does not automatically grant redistribution rights for quotes, news, or statements obtained from third-party sources. Version 0.3.9 depends on akshare-one, FastMCP, and Uvicorn; pinning those versions and testing known samples is more responsible than tracking every release blindly. uvx akshare-one-mcp is the simplest launch path, while a source installation gives teams more control over review and patching.

There is no official paid data tier, commercial data license, or uptime guarantee. Real operating cost includes the host, observability, caching, the selected model API, and potentially a licensed reference feed. The project documents no single global request quota because each upstream can enforce its own rate limit. Production callers should cap concurrency, cache duplicate requests, retry with backoff, and stop rather than hammering a failing source.

Pros

• Focused coverage of common A-share research inputs through a compact nine-tool interface.
• Both stdio and Streamable HTTP support local prototypes and controlled service deployments.
• A clear MIT repository and PyPI release make inspection and version pinning straightforward.
• Works with different MCP hosts and models instead of locking users into one vendor.
• Bilingual setup documentation and a short uvx configuration reduce initial friction.

Cons

• Public upstream data has no unified SLA; schema drift, throttling, delay, and missing values can break automation.
• HTTP mode has no complete built-in identity, tenant, or authorization layer and needs a protective proxy.
• Code licensing and upstream data rights are separate questions, especially for commercial redistribution.
• A model can misread units, reporting periods, adjustment methods, or causality; the server does not validate its conclusions.
• Asset coverage and execution capabilities do not meet professional low-latency trading requirements.

Network availability varies with GitHub, PyPI, and each market source. After installation, queries still require upstream connectivity. Default stdio needs no AKShare-specific API key, but “no key” is not a security feature. If HTTP is enabled, bind it narrowly and add TLS, authentication, quotas, and redacted logs. Never send brokerage credentials, client data, or private positions through an unreviewed model workflow.

Alternatives

FAQ

Is AKShare One MCP Server free?

Yes. The code and package are free under MIT. Model APIs, infrastructure, and licensed market data can still cost money.

Does it require an API key or account?

The documented default tools do not require an AKShare-specific key. Remote HTTP deployments should add their own identity and access control.

Can I use its output for automated trading?

That is not a responsible default. Public data can be delayed or inconsistent, and model-generated analysis can be wrong. Verify against licensed sources and keep execution separate.

How should I handle rate limits?

Limit concurrency, cache repeated calls, use exponential backoff, monitor errors by source, and respect each provider’s terms rather than assuming one shared quota.

Which models work with it?

The server is model-agnostic. Any MCP-compatible host can use it, but smaller models may choose poor parameters or misunderstand financial conventions.

Can news content manipulate an agent?

Potentially. News is untrusted text. Treat it as data, not instructions, and do not give the same agent unrestricted shell, filesystem, or trading permissions.

Bottom Line

AKShare One MCP Server is a useful, narrowly scoped retrieval layer for Chinese stock research. Its strongest qualities are simple installation, relevant tools, and model independence. Its limits are equally important: public upstreams, separate data rights, no built-in production authentication, variable rate limits, and no guarantee that a model’s analysis is correct. Adopt it with pinned versions, sample validation, least-privilege tools, protected networking, and human responsibility for every financial conclusion.