Skip to main content
Glama
WillHsiaoNYC

NYC Open Data Capital Projects MCP Server

by WillHsiaoNYC
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to NYC Open Data Capital Projects MCP Server

No user-submitted related servers found.

    Related Servers

    • Construction MCP Server

      gauravlahoti
      F
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to query live construction project data such as RFIs, submittals, budget variance, daily logs, punch lists, and inspection checklists.
      -
    • Akil MCP by AkilVentures

      Akil MCPofficial

      AkilVentures
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to query NYC public records through a hosted MCP server, supporting civic workflows such as property research, business evaluation, public money tracking, and influence mapping.
      4 npm
      MIT

    • Spurs Analytics MCP

      sirilahari10
      F
      license
      Not graded
      quality
      D
      maintenance
      Governed data pipeline for NBA ticketing and attendance data, exposing typed tools for AI agents to query game performance and seat-tier sales without direct database access.
      -

    • gov-data-mcp

      malonestar
      A
      license
      A
      quality
      A
      maintenance
      A MCP server exposing 95 US government open-data tools as agent-callable tools, enabling direct access to official APIs for environmental, financial, licensing, and infrastructure data with honest run-status reporting.
      8
      15
      101 npm
      MIT
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.7/5.0

    Scored across 18 tools

    Disambiguation4/5

    Tools are cleanly split by domain (schedule vs budget) and by function (detail, history, breakdown, change, duration), so most purposes are distinct. There is mild overlap between rank_projects and project_portfolio (both listing/filtering entities) and between the breakdown/rank tools for aggregate cuts, but the descriptions disambiguate these well enough.

    Naming Consistency4/5

    Names are consistently snake_case throughout. The only deviation is stylistic: some use verb_noun (get_project_schedule, list_agencies, resolve_project_reference, rank_projects) while others are noun-based (schedule_breakdown, dataset_info, project_portfolio), but this remains predictable and readable.

    Tool Count4/5

    18 tools is slightly heavy but justified for a rich analytical domain spanning schedule and budget lenses with detail, history, change, duration, and aggregate operations. Each tool appears to earn its place, with run_sql serving as the general escape hatch.

    Completeness5/5

    The surface covers the full read-only analytical lifecycle: resolution, entity detail, per-period history, breakdowns, period-over-period changes, duration statistics, portfolio listing, rankings, dictionaries, schema/field introspection, and an arbitrary SQL fallback. No obvious gaps for a read-only open-data server.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources