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丝路E投财务引擎 MCP 适配层

by chang0911

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    • F
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      C
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      Stateless MCP adapter for the LKPlanWise Go REST API, enabling AI agents to call curated financial tools via Streamable HTTP while forwarding bearer credentials.
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    • F
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      Exposes 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.
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    • A
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      Enables natural-language access to 25 Tonghuashun (Iwencai) financial skills, covering market data queries, cross-asset screening, and news/announcement/research searches through two HTTP endpoints.
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    TDQS

    A3.6/5.0

    Scored across 21 tools

    Disambiguation4/5

    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.

    Naming Consistency3/5

    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.

    Tool Count3/5

    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.

    Completeness4/5

    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).

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues