Skip to main content
Glama
HemanthDonga

hedra-mcp-server

by HemanthDonga
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Related Servers

Alternatives to hedra-mcp-server

No user-submitted related servers found.

    Related Servers

    • fal.ai MCP Server

      M1Vision
      A
      license
      Not graded
      quality
      D
      maintenance
      Enables interaction with fal.ai AI models through MCP, supporting model discovery, content generation, queue management, and file uploads to the fal.ai platform.
      MIT
    • GPTProto MCP by gptproto-ai

      GPTProto MCPofficial

      gptproto-ai
      A
      license
      A
      quality
      C
      maintenance
      Enables AI hosts to discover GPTProto models, retrieve live pricing, make documented API requests, submit custom generations, and poll asynchronous tasks through local MCP tools.
      9
      16 npm
      MIT
    • maginary-mcp by maginaryai

      maginary-mcpofficial

      maginaryai
      A
      license
      A
      quality
      B
      maintenance
      Enables MCP-compatible clients to discover Maginary's image/video generation flags, submit generation requests, and poll for results, including support for API-key and OAuth authentication.
      13
      47 PyPI
      1
      MIT

    • semantic-runtime

      Chloride233
      A
      license
      Not graded
      quality
      A
      maintenance
      Enables MCP clients to serve and query semantic models, providing tools for entity descriptions, metric lookups, context resolution, and operation validation for AI agents.
      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

    A4.7/5.0

    Scored across 14 tools

    Disambiguation5/5

    Each tool targets a distinct resource and action: discovery, upload, schema retrieval, cost estimation, submission, job retrieval, status polling, waiting, listing, and billing. Related job-monitoring tools (get_job, get_job_status, wait_for_job) are clearly differentiated by purpose and response detail, with descriptions explicitly guiding selection.

    Naming Consistency5/5

    All tool names follow a consistent snake_case verb_noun pattern (e.g., hedra_list_models, hedra_submit_job, hedra_get_balance). Multi-word objects like get_model_input_schema and list_model_jobs are constructed uniformly, making the tool surface predictable and easy to navigate.

    Tool Count5/5

    14 tools is well-scoped for a media generation API, covering model discovery, input schema, file upload, cost estimation, job submission, monitoring, listing, and wallet/usage checks. Each tool serves a necessary step in the workflow without unnecessary redundancy.

    Completeness5/5

    The tool set covers the full generation lifecycle: discover models, inspect schemas, upload media, estimate cost, submit jobs, wait/poll for completion, retrieve outputs, and list historical jobs. Billing and usage tracking are also included, leaving no critical gaps for the core API workflows.

    Maintenance

    ActivityStale
    ResponsivenessNo issues

    Resources