丝路E投财务引擎 MCP 适配层
Related Servers
Alternatives to 丝路E投财务引擎 MCP 适配层
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceStateless MCP adapter for the LKPlanWise Go REST API, enabling AI agents to call curated financial tools via Streamable HTTP while forwarding bearer credentials.-
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to query Chinese A-share market data — real-time quotes, K-lines, order books, financials, fund flows, dragon-tiger lists, sectors, convertible bonds, macro data, and factor screening — through 24 tools, five of which require no API key. It can be used via a hosted endpoint with no installation or self-hosted locally over stdio.MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to pull end-of-day and historical stock prices, ticker metadata with available date ranges, crypto pair prices at a chosen resample frequency, and recent financial news filtered by ticker or tag. Runs either against a hosted gateway endpoint or locally over stdio, with API-key handling for the account tiers each data source requires.86 npmMIT
- AlicenseNot gradedqualityAmaintenanceExposes fourteen read-only tools over the HEY Research public API, letting assistants look up Robinhood Chain projects, builders, shipped work, relationships and market context, with each answer tagged FACT, DERIVED or UNKNOWN and unmeasured fields omitted rather than zeroed. Runs over stdio or hosted Streamable HTTP, and gives no trade instructions.MIT
- FlicenseNot gradedqualityBmaintenanceExposes 38 tools over stdio that let an AI agent read simulated banking data, run financial and economic analyses, manage goals and preferences, and switch user contexts. It also lets the agent compose, validate, and edit declarative UI dashboards from a fixed catalog of 15 typed React components, so the interface is generated on the fly instead of hardcoded.-
- AlicenseNot gradedqualityBmaintenanceEnables secure exposure of internal tools to LLM clients with API-key authentication, tenant isolation, per-tool guardrails, PII scrubbing, rate limiting, audit logging, and telemetry over stdio and HTTP/SSE.MIT
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).