丝路E投财务引擎 MCP 适配层
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- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to query 250+ financial data tools spanning stocks, ETFs, cryptocurrencies, forex, commodities, economics, technical indicators, and SEC filings. Supports dynamic, static, and all-tools modes over HTTP/SSE transport, with hosted or self-hosted deployment via npm and Docker.601 npmApache 2.0
- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to query and analyze financial data through 250+ tools spanning stocks, ETFs, crypto, forex, commodities, economics, company fundamentals, SEC filings, and market news. It supports dynamic, static, or full toolset loading with hosted or self-hosted HTTP/SSE deployment.601 npmApache 2.0
- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to access and analyze 250+ financial data tools covering stocks, ETFs, crypto, forex, commodities, economics, and more, with runtime toolset management and hosted or self-hosted HTTP/SSE deployment.601 npmApache 2.0
- AlicenseAqualityCmaintenanceEnables developers to expose product operations as model-callable tools over stdio or Streamable HTTP with bearer-token auth, per-client rate limits, host allow-listing, structured call logging, and a swappable backend for secure, testable deployments.3MIT
- AlicenseNot gradedqualityAmaintenanceExposes 250+ financial data tools across 24 categories to AI assistants, covering stocks, ETFs, crypto, forex, commodities, economics, company fundamentals, financial statements, technical indicators, and SEC filings. Supports dynamic toolset loading, static pre-loading, and hosted or self-hosted deployment over HTTP/SSE.601 npmApache 2.0
- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to access and analyze financial data, stock information, company fundamentals, and market insights through 250+ tools covering equities, ETFs, crypto, forex, commodities, and economics. It supports dynamic toolset loading and can be hosted or self-hosted over HTTP/SSE.601 npmApache 2.0
TDQS
Scored across 21 tools
Most tools have a clearly distinct output (JSON reports vs Excel vs dashboard vs Word/PPT vs pipeline), so the agent can often tell them apart. However, several tools share the identical '5类输入txt' input and similar names (fast_calc_reports, fast_calc_excel, run_delivery_bundle; estimate_etou_json vs estimate_excel), and the two instruction readers (get_protocol_instructions vs get_skill_instructions) could be confused, though the descriptions do help resolve this.
There is a strong verb_noun convention for most tools (query_usage, get_*, run_*, generate_*, submit_feedback). But a competing 'domain-prefix + artifact' convention exists (fast_calc_reports, fast_calc_excel, estimate_excel, permitted_cost_excel, ppt_extract_data), so the surface mixes two readable but different patterns.
21 tools is borderline heavy for a single server and reflects a broad suite spanning estimation, pricing, national econ, reporting, checks and solving. Each tool maps to a specific artifact, but the count pushes toward the '16-25 feels heavy' band and includes some near-duplicative output variants.
The surface covers a full financial-modeling lifecycle: protocol/skill instructions, data extraction and matching, calculation, solving, uncertainty, delivery bundles, Word/PPT/dashboard output, model and revenue checks, usage stats and feedback. Only minor gaps remain (e.g. no explicit lifecycle delete/update semantics, and some verification depends on external benchmark lookups).