Skip to main content
Glama
AIops-tools

AI Guardian

by AIops-tools
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to AI Guardian

No user-submitted related servers found.

    Related Servers

    • local-llm-mcp

      primal79
      A
      license
      A
      quality
      C
      maintenance
      Enables a cloud orchestrator to query a local Ollama model over Tailscale or a LAN as a side-channel for drafts, summaries, and other helper output, with tools to list available models and to redact text. Answers leaving the server are passed through output-only DLP that masks card numbers, IBANs, emails, phone numbers, API keys, and similar secrets before they reach the cloud.
      3
      MIT

    • claude-token-saver-mcp

      BlackFoil
      A
      license
      A
      quality
      C
      maintenance
      Enables Claude Code to offload routine code generation and text processing tasks to a local Ollama LLM, saving Cloud API tokens and costs with automatic model selection and security features.
      11
      77
      4
      Apache 2.0

    • agent-sudo-mcp

      Kisyntra
      A
      license
      A
      quality
      A
      maintenance
      Local zero-trust permission gateway for AI agents. Enforces policy-based tool authorization, human approvals, scoped permissions, and cryptographically verifiable audit logs.
      4
      5
      Apache 2.0

    • Ollama MCP Server

      etnlbck
      A
      license
      Not graded
      quality
      D
      maintenance
      Enables interaction with locally running Ollama models through chat, generation, and model management operations. Supports listing, downloading, and deleting models while maintaining conversation history for interactive sessions.
      203
      MIT
    Deploy Server
    RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

    TDQS

    A3.6/5.0

    Scored across 21 tools

    Disambiguation4/5

    Most tools target distinct resources/actions (models, prompts, policies, usage, undo), and the [READ]/[WRITE] tags plus descriptions separate them. Some overlap exists among list_models, policy_view, model_provenance, and anomaly_report, and between guarded_generate and observe_chat, but the descriptions clarify the differences.

    Naming Consistency3/5

    All names are snake_case and readable, but conventions are mixed: imperative verbs (pull_model, set_model_allowlist), noun phrases (server_status, vram_usage, anomaly_report), and gerund/adjective forms (running_models, guarded_generate). The lack of a consistent read/write naming pattern makes the set less predictable than a uniform verb_noun convention.

    Tool Count3/5

    At 21 tools this is on the heavy side, even though the governance domain spans model inventory, policy, guarded inference, monitoring, and undo. Most tools have a distinct job, but the surface is large enough that an agent must navigate many niche endpoints, putting it in the borderline range.

    Completeness4/5

    The core governance lifecycle is covered: model management, policy/provenance, guarded inference, usage monitoring, and undo. Gaps include no tool to manage configured Ollama targets or set global default block thresholds, and no way to clear/export usage history, but these are workarounds rather than dead ends.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

    Resources