Skip to main content
Glama
lealvona

local-llm-mcp

by lealvona
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to local-llm-mcp

No user-submitted related servers found.

    Related Servers

    • local-llm

      avtplay
      F
      license
      Not graded
      quality
      C
      maintenance
      Enables delegating mechanical or high-volume subtasks to a local LLM through an MCP tool, letting the assistant query the local model without using its own output tokens for content.
      -

    • CascadeGateway

      jadberro
      A
      license
      A
      quality
      A
      maintenance
      Provides an MCP endpoint that lets clients like Google Antigravity and Claude Desktop dispatch LLM tasks to local GPU models with automatic hardware-adaptive routing and cloud fallback, enabling near-zero token cost execution.
      2
      3
      4
      MIT

    • llm-localfirst

      shaxzodbek-uzb
      A
      license
      Not graded
      quality
      B
      maintenance
      A local-first LLM routing MCP server that keeps sensitive data on your own models, with fail-closed privacy and manager-worker delegation, exposing route and complete tools to any MCP client.
      MIT

    • pseudonym-mcp

      woladi
      A
      license
      A
      quality
      A
      maintenance
      Local pseudonymisation MCP server that detects PII in text, replaces it with opaque tokens before sending to cloud LLMs, and restores tokens afterward.
      2
      199 npm
      2
      MIT

    • mcp-local-llama

      chrishorne74
      A
      license
      Not graded
      quality
      B
      maintenance
      MCP server that delegates mechanical tasks like summarization, classification, extraction, and drafting to a local Llama.cpp LLM, serving as a cost-optimization layer while Claude handles reasoning and quality control.
      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

    A4.3/5.0

    Scored across 8 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes—delegate handles text/file analysis, run digests shell output, artifact slices raw material, and status reports state. However, delegate and run both accept commands, and enable vs set_mode both touch activation/mode, creating occasional ambiguity.

    Naming Consistency3/5

    The shared local_llm_ prefix gives the set a strong family resemblance, but the second word is inconsistent: nouns (artifact, disclosure, status), verbs (compact, delegate, enable, run), and one verb-noun (set_mode) are mixed rather than following a single pattern.

    Tool Count5/5

    8 tools is a well-scoped size for a local LLM proxy server. Each tool maps to a distinct part of the workflow—opt-in, mode control, delegation, shell digestion, artifact access, memory compaction, disclosure settings, and status—without redundancy.

    Completeness4/5

    The set covers the full lifecycle: enabling the server, switching modes, delegating over text/files/commands, retrieving raw artifacts, compacting memory, and checking status. Minor gaps like explicit cancellation or artifact list/delete are workable since calls are synchronous digests and status exposes artifact counts.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources