AgentHubAgentHub

mcp-local-rag MCP Setup & Guide

MCP ServerMCP RegistryOfficial

io.github.shinpr/mcp-local-rag · v0.21.0

Easy-to-setup local RAG server with minimal configuration

Copy the install config on this page first, then verify docs and permissions upstream.

Overview

Easy-to-setup local RAG server with minimal configuration mcp-local-rag is a MCP Server listed from MCP Registry. Transports: stdio. This page includes an overview, setup tutorial, install commands, and use cases for Trae, Tongyi Lingma, Cursor, Claude Code, and VS Code.

Use cases

AgentHub Verified AvailabilityTested & Ready

Automated pipeline validated install commands, protocol & client compatibility

Verified At2026-10-04
Install Snippets TestedCLI & JSON config syntax verified
Protocol Handshake ReadyComplies with JSON-RPC 2.0 specifications
Origin Registry ActiveSourced from official-mcp-registry
Verified ClientsClaude Code、Claude Desktop、Cursor 等
Security Tier: A+ 级 · 官方认证推荐 (A+)·Maintained by official/verified teams, audited for standard MCP protocol compliance.

Copy by platform

Choose your platform

  1. Open or create .cursor/mcp.json in your project root
  2. Click Copy config and paste; merge only this mcpServers entry if others exist
  3. Replace <placeholders> in env with real secrets (see Environment variables below)
  4. Save, then Cmd+Shift+P → Reload Window

Pre-fill Environment Variables (Optional)

Privacy Guarantee: Keys are replaced 100% locally in your browser memory and are NEVER uploaded or stored on any server.
Click to copy snippet
{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-local-rag"
      ]
    }
  }
}

Setup tutorial

  1. Open the mcp-local-rag page and confirm this MCP Server (source: MCP Registry).
  2. Copy the Cursor, Claude Code, or VS Code snippet.
  3. Merge it into mcpServers and replace env placeholders with real secrets.
  4. Reload the window, then call the MCP tools from your agent chat.

Install commands

Install commands and setup steps are in the HTML so search engines and no-JS browsers can read them without running client JavaScript.

Claude Code (local)

  1. Install Claude Code CLI
  2. Copy the command below, replace <placeholders> with real env values, then run in terminal
  3. See Environment variables below if listed
claude mcp add mcp-local-rag -- npx -y mcp-local-rag

Cursor — .cursor/mcp.json (local)

  1. Open or create .cursor/mcp.json in your project root
  2. Click Copy config and paste; merge only this mcpServers entry if others exist
  3. Replace <placeholders> in env with real secrets (see Environment variables below)
  4. Save, then Cmd+Shift+P → Reload Window
{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-local-rag"
      ]
    }
  }
}

VS Code — .vscode/mcp.json (local)

  1. Install GitHub Copilot in VS Code with MCP support
  2. Open or create .vscode/mcp.json in your project root
  3. Click Copy config and paste; merge only this mcpServers entry if others exist
  4. Replace <placeholders> in env with real secrets
  5. Save and Developer: Reload Window
{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-local-rag"
      ]
    }
  }
}

Claude Desktop — claude_desktop_config.json (local)

  1. Open Claude Desktop claude_desktop_config.json (see remote guide for paths)
  2. Click Copy config and merge under mcpServers
  3. Replace <placeholders> in env with real secrets
  4. Fully quit and restart Claude Desktop
{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-local-rag"
      ]
    }
  }
}

Trae — .trae/mcp.json (local)

  1. Trae → Settings → MCP, or edit .trae/mcp.json / global mcp.json
  2. Click Copy config and merge mcpServers
  3. Replace <placeholders> in env with real secrets
  4. Save and reload Trae
{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-local-rag"
      ]
    }
  }
}

Cherry Studio — MCP settings (local)

  1. Cherry Studio → Settings → MCP Servers → Add (STDIO)
  2. Or import JSON: click Copy config and merge mcpServers
  3. Replace <placeholders> in env; ensure Node.js / uv (npx, uvx) are installed
  4. Enable the server and check tools load
{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-local-rag"
      ]
    }
  }
}

Tongyi Lingma — MCP config (local)

  1. Lingma Settings → MCP → + → STDIO or config file
  2. Click Copy config and merge mcpServers
  3. Replace <placeholders> in env; need Node.js 18+ (npx) or uv (uvx)
  4. Confirm connected before using tools in agent chat
{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-local-rag"
      ]
    }
  }
}

Windsurf — mcp_config.json (local)

  1. Edit ~/.codeium/windsurf/mcp_config.json
  2. Click Copy config and merge mcpServers (stdio same as Cursor)
  3. Replace <placeholders> in env, save, refresh Cascade
{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-local-rag"
      ]
    }
  }
}

Cline — MCP Servers (local)

  1. Cline panel → Settings → MCP Servers
  2. Click Copy config and merge
  3. Replace <placeholders> in env, then save
{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-local-rag"
      ]
    }
  }
}

WorkBuddy — .workbuddy/mcp.json (local)

  1. Edit ~/.workbuddy/mcp.json (user) or project .workbuddy/mcp.json
  2. Or Plugins → MCP Servers → Configure MCP and paste the JSON below
  3. Replace <placeholders> in env; on Windows prefer absolute paths for command/scripts
  4. Save, restart WorkBuddy, confirm connector status is green
{
  "mcpServers": {
    "mcp-local-rag": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-local-rag"
      ]
    }
  }
}

Troubleshooting & Common ErrorsFAQ

Common connection errors and verified fixes for mcp-local-rag

Getting 'connection closed' or exit code 1 in Cursor / Claude Code for mcp-local-rag?

Usually caused by missing runtime paths or IDE environment inheritance. Fix steps: 1. Verify Node.js 18+ (npx) or Python 3.10+ (uvx) is installed; 2. Run 'which npx' or 'which uvx' in terminal, and replace 'command' with absolute path; 3. Reload or restart the client window after modifying config.

Fix Snippet
# Check binary path in terminal:
which npx
node -v
Getting 'spawn npx ENOENT' or 'command not found'?

The editor background process does not inherit your full terminal PATH. Solution: Globally install the package, or set the absolute binary path (e.g. C:\Program Files\nodejs\npx.cmd on Windows, or /usr/local/bin/npx on macOS).

Missing required environment variable or authentication failure?

mcp-local-rag requires environment variables (BASE_DIR、BASE_DIRS、DB_PATH、CACHE_DIR、HF_ENDPOINT、MODEL_NAME、MAX_FILE_SIZE、RAG_MAX_DISTANCE、RAG_GROUPING、RAG_MAX_FILES、CHUNK_MIN_LENGTH、STORE_IMAGES、EMBED_TITLE_PREFIX、EMBED_HEADING_PREFIX、RAG_DEVICE、RAG_DTYPE、RAG_HYBRID_WEIGHT、RAG_RERANK_CMD、RAG_RERANK_TIMEOUT_MS). Ensure you have added valid keys under the 'env' object in your config file without trailing whitespace.

Fix Snippet
// .cursor/mcp.json 或 claude_desktop_config.json
{
  "env": {
    "API_KEY": "your_actual_key_here"
  }
}

Tool Mock Playground

Sandbox

mcp-local-rag Tool Interface Simulation · Preview tool schema & outputs without local runtime

Sandbox Ready
fn: mcp_local_ragExecute the core tool interface of mcp-local-rag
Request ArgumentsJSON Schema
{
  "target": "mcp-local-rag",
  "action": "execute",
  "options": {
    "mode": "standard",
    "timeoutMs": 5000
  }
}
💡Parameters generated dynamically by Agent runtime
Agent Tool Output

Click 'Run Mock' above

to preview the raw response returned to the LLM

Env: AgentHub Virtual SandboxJSON-RPC 2.0

Decision Guide: Why & When to Use

Assess suitability before installing to save trial-and-error time

Best Suited For
  • PR review
  • Changelog generation
  • Cross-repo issue search
When NOT to Use
  • Replacing human security audit
  • Unauthorized repo access
Recommended Workflow Pairing:View Scenario →

mcp-local-rag + Scenario Prompt → Complete Agent Automation

MCP hands-on: install to visible results

Follow the full lab (expected UI/output + contrast checks). After installing this item, verify with the tutorial prompts.

Open tutorial →

Related resources

Often paired with

Keep exploring AgentHub

Most people compare similar tools or check scenario guides before installing—start here.

Listing badge: put AgentHub on your site

Copy either snippet into your project homepage, docs, or GitHub README. The badge is a hotlinked SVG — nothing to host — and it links back to this page so visitors can find the install steps.

PreviewListed on AgentHub: mcp-local-rag
HTML
<a href="https://myagenthub.cn/p/io.github.shinpr/mcp-local-rag" title="Listed on AgentHub: mcp-local-rag" target="_blank" rel="noopener">
  <img src="https://myagenthub.cn/badge/io.github.shinpr/mcp-local-rag?lang=en" alt="Listed on AgentHub: mcp-local-rag" height="20" style="border:0"/>
</a>
Markdown (GitHub README)
[![Listed on AgentHub: mcp-local-rag](https://myagenthub.cn/badge/io.github.shinpr/mcp-local-rag?lang=en)](https://myagenthub.cn/p/io.github.shinpr/mcp-local-rag)

Badges are generated on the fly from /badge/<package-id>, so name and listing changes propagate automatically. Keep the link target unchanged — it is what counts as the referral.

Unified Manifest

{
  "id": "io.github.shinpr/mcp-local-rag",
  "type": "mcp-server",
  "version": "0.21.0",
  "displayName": "mcp-local-rag",
  "description": "Easy-to-setup local RAG server with minimal configuration",
  "repository": {
    "url": "https://github.com/shinpr/mcp-local-rag",
    "source": "github"
  },
  "distribution": {
    "packages": [
      {
        "registryType": "npm",
        "identifier": "mcp-local-rag",
        "version": "0.21.0",
        "transport": "stdio",
        "environmentVariables": [
          {
            "name": "BASE_DIR",
            "description": "Base directory for document storage (defaults to current working directory). Ignored when BASE_DIRS is set."
          },
          {
            "name": "BASE_DIRS",
            "description": "JSON array of base directories (e.g. '[\"/a\",\"/b\"]'). Takes precedence over BASE_DIR."
          },
          {
            "name": "DB_PATH",
            "description": "Path to LanceDB database directory (defaults to ./lancedb/)"
          },
          {
            "name": "CACHE_DIR",
            "description": "Directory where Transformers.js models are cached (defaults to ./models/)"
          },
          {
            "name": "HF_ENDPOINT",
            "description": "Hugging Face model download endpoint. Set this to a mirror URL when direct downloads are blocked (defaults to https://huggingface.co)."
          },
          {
            "name": "MODEL_NAME",
            "description": "Embedding model name (defaults to Xenova/all-MiniLM-L6-v2)"
          },
          {
            "name": "MAX_FILE_SIZE",
            "description": "Maximum file size in bytes (defaults to 104857600 / 100MB)"
          },
          {
            "name": "RAG_MAX_DISTANCE",
            "description": "Maximum distance threshold for filtering search results. Results with distance greater than this value will be excluded. Lower values mean stricter filtering (e.g., 0.5 for high relevance only)"
          },
          {
            "name": "RAG_GROUPING",
            "description": "Grouping mode for quality filtering. 'similar' returns only the most similar group (stops at first distance jump). 'related' includes related groups (stops at second distance jump). Unset means no grouping filter"
          },
          {
            "name": "RAG_MAX_FILES",
            "description": "Maximum number of files to keep in search results. Results are filtered to include only chunks from the top N best-scoring files. For example, 1 returns only the single best-matching file's chunks. Unset means no file filtering."
          },
          {
            "name": "CHUNK_MIN_LENGTH",
            "description": "Minimum chunk length in characters (1-10000, defaults to 50). Chunks shorter than this threshold are filtered out during ingestion."
          },
          {
            "name": "STORE_IMAGES",
            "description": "Store supported PDF and DOCX images during ingestion and return them with matched chunks (defaults to false)."
          },
          {
            "name": "EMBED_TITLE_PREFIX",
            "description": "Embed each chunk together with its document title, which can help when passages don't restate the topic the title names (defaults to false). After changing it, use a new DB_PATH or delete the index and re-ingest."
          },
          {
            "name": "EMBED_HEADING_PREFIX",
            "description": "Add section headings to chunk embeddings when they fit (defaults to false). Independent of EMBED_TITLE_PREFIX. Re-ingest documents after changing it."
          },
          {
            "name": "RAG_DEVICE",
            "description": "Execution device for the embedder (defaults to cpu). Passed straight to ONNX Runtime; see the Transformers.js device source for the supported backend names. If the requested device fails to initialize, the server throws an error."
          },
          {
            "name": "RAG_DTYPE",
            "description": "Embedding quantization dtype for the embedder (defaults to fp32). Opt-in and pass-through; accepts any dtype the chosen model provides (fp32, fp16, q8, int8, ...). If the model has no variant for the requested dtype, the server throws an error. Changing this changes the embedding space — re-ingest existing data."
          },
          {
            "name": "RAG_HYBRID_WEIGHT",
            "description": "Keyword boost factor for hybrid search (0.0-1.0, defaults to 0.6). 0 means semantic similarity only; higher values increase the keyword-match contribution to the final score."
          },
          {
            "name": "RAG_RERANK_CMD",
            "description": "External reranker command template. Use {query} and {top} for query text and result count; unset disables reranking."
          },
          {
            "name": "RAG_RERANK_TIMEOUT_MS",
            "description": "Time budget per rerank call in milliseconds (100-600000, defaults to 10000). On timeout the spawned command is killed and the pre-rerank ordering is returned."
          }
        ]
      }
    ],
    "remotes": []
  },
  "dependencies": [],
  "installTargets": [
    "claude-code",
    "claude-desktop",
    "cursor",
    "vscode",
    "trae",
    "cherry-studio",
    "lingma",
    "windsurf",
    "cline",
    "workbuddy"
  ],
  "keywords": [],
  "provenance": {
    "origin": "official-mcp-registry",
    "originalId": "io.github.shinpr/mcp-local-rag",
    "originalUrl": "https://registry.modelcontextprotocol.io/v0.1/servers/io.github.shinpr%2Fmcp-local-rag/versions/latest",
    "isOfficial": true,
    "status": "active"
  }
}