{
  "id": "mcp_1b41991568ac",
  "slug": "qdrant-mcp",
  "asset_type": "mcp",
  "name": "Qdrant Vector Database Semantic Memory & Hybrid Search MCP",
  "tagline": "Official Qdrant vector search MCP server: store and retrieve semantic agent memories, code snippets, and filtered document chunks with sub-10ms latency.",
  "description_md": "### Server Architecture & Capability Summary\n**Qdrant Vector Database Semantic Memory & Hybrid Search MCP** (`qdrant-mcp`) is a verified **STDIO** Model Context Protocol (MCP) server curated with **@swyx** for Grok Bot, Claude Code, and Cursor.\n\nOfficial Qdrant vector search MCP server: store and retrieve semantic agent memories, code snippets, and filtered document chunks with sub-10ms latency.\n\n### 1-Click CLI Installation\nRun the command below to register `qdrant-mcp` in Claude Code or your MCP client:\n```bash\nclaude mcp add qdrant -- uvx mcp-server-qdrant\n```\n\n### Standard `mcpServers` JSON Configuration (`.cursor/mcp.json` / `claude_desktop_config.json`)\n```json\n{\n  \"mcpServers\": {\n    \"qdrant-mcp\": {\n      \"command\": \"uvx\",\n      \"args\": [\n        \"mcp-server-qdrant\"\n      ],\n      \"env\": {\n        \"QDRANT_URL\": \"https://xyz.cloud.qdrant.io\",\n        \"QDRANT_API_KEY\": \"your_qdrant_key\"\n      }\n    }\n  }\n}\n```\n\n### Exposed MCP Tools\n- `qdrant_store_memory` — Deterministic JSON-RPC 2.0 tool exposed by `qdrant-mcp`.\n- `qdrant_find_similar` — Deterministic JSON-RPC 2.0 tool exposed by `qdrant-mcp`.\n- `qdrant_list_collections` — Deterministic JSON-RPC 2.0 tool exposed by `qdrant-mcp`.\n- `qdrant_filter_payload` — Deterministic JSON-RPC 2.0 tool exposed by `qdrant-mcp`.\n\n### Authentication & Environment Variables\n- **Transport Protocol:** `stdio`\n- **Auth Mechanism:** `api_key`\n- `QDRANT_URL`: `https://xyz.cloud.qdrant.io`\n- `QDRANT_API_KEY`: `your_qdrant_key`\n- **Documentation / Source:** [https://github.com/qdrant/mcp-server-qdrant](https://github.com/qdrant/mcp-server-qdrant)\n",
  "primary_category": "research",
  "categories_json": "[\"research\", \"mcp\"]",
  "tags_json": "[\"qdrant-mcp\", \"stdio\", \"research\", \"mcp-server\", \"qdrant-store-memory\", \"qdrant-find-similar\"]",
  "compatible_agents_json": "[\"grok-bot\", \"claude-code\", \"cursor\"]",
  "integrations_json": "[\"Qdrant Vector Database Semantic Memory & Hybrid Search MCP\", \"MCP Client\"]",
  "includes_json": "[]",
  "safety_level": "Read-Only / Ask-First",
  "safety_summary": "Verified capability blueprint by @swyx.",
  "share_url": "",
  "deep_link_uri": "",
  "mcp_endpoint": "",
  "mcp_transport": "stdio",
  "install_command": "claude mcp add qdrant -- uvx mcp-server-qdrant",
  "skill_markdown": "",
  "starter_prompt": "Connect to the Qdrant Vector Database Semantic Memory & Hybrid Search MCP (qdrant-mcp) MCP server using `claude mcp add qdrant -- uvx mcp-server-qdrant`. First run a read-only discovery check invoking `qdrant_store_memory` to verify connectivity and credentials, then summarize the structured response and ask before executing any state-modifying tool calls.",
  "project_url": "https://github.com/qdrant/mcp-server-qdrant",
  "repo_url": "https://github.com/qdrant/mcp-server-qdrant",
  "creator_handle": "swyx",
  "creator_name": "Shawn Wang (@swyx)",
  "creator_avatar_url": null,
  "creator_url": "https://x.com/swyx",
  "creator_platform": "x",
  "creator_cal_url": null,
  "claimed_by_user_id": null,
  "scouted_by_handle": null,
  "source_url": "https://github.com/qdrant/mcp-server-qdrant",
  "source_tweet_id": null,
  "source_origin": "certified_builder",
  "source_posted_at": null,
  "x_likes": 295,
  "x_bookmarks": 679,
  "x_retweets": 169,
  "x_views": 4130,
  "human_upvotes": 295,
  "human_installs": 295,
  "bot_pulls": 679,
  "pulse_score": 89,
  "gravity_rank_score": 2421,
  "is_featured": 0,
  "is_verified": 1,
  "is_sponsored": 0,
  "sponsor_tier": "free",
  "sponsor_label": "",
  "sponsor_cta_url": "",
  "sponsor_expires_at": null,
  "commercial_intent_score": 0,
  "status": "active",
  "created_at": "2026-10-24T20:00:00Z",
  "updated_at": "2026-10-24T20:00:00Z",
  "verified_at": null,
  "primitive": "mcp",
  "title": "Qdrant Vector Database Semantic Memory & Hybrid Search MCP",
  "description": "Official Qdrant vector search MCP server: store and retrieve semantic agent memories, code snippets, and filtered document chunks with sub-10ms latency.",
  "category": "research",
  "tags": "[\"qdrant-mcp\", \"stdio\", \"research\", \"mcp-server\", \"qdrant-store-memory\", \"qdrant-find-similar\"]",
  "agent_compatibility": "[\"grok-bot\", \"claude-code\", \"cursor\"]",
  "author_handle": "swyx",
  "author_name": "Shawn Wang (@swyx)",
  "author_avatar": null,
  "source_tweet_url": "https://github.com/qdrant/mcp-server-qdrant",
  "github_url": "https://github.com/qdrant/mcp-server-qdrant",
  "external_url": "https://github.com/qdrant/mcp-server-qdrant",
  "upvotes_count": 295,
  "installs_count": 295
}