Skip to main content
Glama
Sign In
Run:AI MCP Server

Run:AI MCP Server

by sejongjeong
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Related Servers

Alternatives to Run:AI MCP Server

No user-submitted related servers found.

    Related Servers

    • agent-control

      loulanyue
      A
      license
      Not graded
      quality
      A
      maintenance
      Enables LLMs to orchestrate AI agents and tasks, inspect DAG workflows, monitor cluster metrics, and perform safe database queries and statements through standardized MCP tools.
      189
      Apache 2.0

    • agentic-ai-devops

      satyajeetkumarsing
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables LLM agents to connect to multi-cloud DevOps control planes for Terraform plan inspection, drift detection and remediation, cost estimation, incident triage, and cloud resource discovery across Azure, AWS, and GCP. It supports autonomous workflows for PR review, FinOps optimization, and self-healing operations through MCP tools.
      MIT

    • Relay

      adarshp14
      A
      license
      Not graded
      quality
      D
      maintenance
      Enables AI agents to access a unified catalog of tools from various APIs (OpenAPI, GraphQL, MCP, Google Discovery) through the MCP protocol.
      7 npm
      MIT

    • mcp-nvidia-nim

      luizGDpulz
      A
      license
      C
      quality
      B
      maintenance
      Enables AI assistants and agents to query and orchestrate NVIDIA NIM cloud models for deep reasoning, code review, multimodal vision analysis, document extraction, and status checks through MCP tools, with built-in rate limiting and model alias resolution.
      11
      MIT

    • server-vault

      SikeFix
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to securely manage server credentials, execute commands, inspect and rotate passwords, discover websites and containers, and access GPU/NPU status through permission-scoped MCP tools and REST endpoints.
      1
      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

    A4.4/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a distinct responsibility: searching the API spec, executing API calls, resolving names to IDs, and running CLI-only operations. There is no overlap; dependencies like 'search before call' are explicitly documented.

    Naming Consistency5/5

    All tool names follow a consistent verb_runai_noun pattern with snake_case: search_runai_api_spec, call_runai_api, resolve_runai_names, execute_runai_cli. The naming is uniform and predictable.

    Tool Count5/5

    With only 4 tools, the server covers an enormous API surface by using a meta-design (search + call + resolve + CLI). Each tool is essential and well-scoped, avoiding redundancy.

    Completeness5/5

    The toolset provides comprehensive coverage: search_runai_api_spec exposes every API endpoint, call_runai_api executes them, resolve_runai_names bridges user-friendly names to API IDs, and execute_runai_cli handles operations impossible via API (port-forward, exec, logs). No obvious gaps.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

    Resources