{"data":{"slug":"giancarloerra-socraticode","name":"SocratiCode","tagline":"Enterprise-grade codebase intelligence with local setup, hybrid semantic search, and polyglot dependency graphs","github_url":"https://github.com/giancarloerra/SocratiCode","owner":"giancarloerra","repo":"SocratiCode","owner_avatar_url":"https://avatars.githubusercontent.com/u/105157948?v=4","primary_language":"TypeScript","stars":3263,"forks":409,"topics":["ai","ai-assistant","ast","claude","claude-code","code-graph","codebase-intelligence","context-engine","docker","embeddings","gemini","gemini-cli-extension","mcp","openai","qdrant","semantic","semantic-search","vector-database","vector-embeddings","vector-search"],"archived":false,"github_pushed_at":"2026-08-14T17:39:58+00:00","maintenance_label":"Very active","stars_delta_30d":131,"url":"https://www.graphcanon.com/tools/giancarloerra-socraticode","markdown_url":"https://www.graphcanon.com/tools/giancarloerra-socraticode.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/giancarloerra-socraticode","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=giancarloerra-socraticode","description":"Enterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP: hybrid semantic search, polyglot dependency graphs, symbol-level impact analysis & call-flow, interactive HTML viewer, cross-project & branch-aware search, DB/API/infra knowledge. 61% less tokens, 84% fewer calls, 37x faster. Cloud in beta.","homepage_url":"https://socraticode.cloud","license":"AGPL-3.0","open_issues":5,"watchers":19,"ai_summary":"SocratiCode offers advanced capabilities for code analysis including symbol-level impact analysis, cross-project and branch-aware search. Integrates with various AI frameworks like Claude and Gemini.","readme_excerpt":"## Quick Start\n\n> **Only [Docker](https://www.docker.com/products/docker-desktop/) (running) required.**\n\n**One-click install** — Claude Code, VS Code and Cursor:\n\n\n   \n\n**All MCP hosts** — add the following to your `mcpServers` (Claude Desktop, Windsurf, Cline, Roo Code) or `servers` (VS Code project-local `.vscode/mcp.json`) config:\n\n```json\n\"socraticode\": {\n  \"command\": \"npx\",\n  \"args\": [\"-y\", \"socraticode\"]\n}\n```\n\n**Claude Code** — install the plugin (recommended, includes workflow skills for best results):\n\nFrom your shell:\n\n```bash\nclaude plugin marketplace add giancarloerra/socraticode\nclaude plugin install socraticode@socraticode\n```\n\nOr from within Claude Code:\n\n```\n/plugin marketplace add giancarloerra/socraticode\n/plugin install socraticode@socraticode\n```\n\n> **Auto-updates:** After installing, enable automatic updates by opening `/plugin` → Marketplaces → select `socraticode` → Enable auto-update.\n\nOr as MCP only (without skills):\n\n```bash\nclaude mcp add socraticode -- npx -y socraticode\n```\n\n> **Updating:** `npx` caches the package after the first run. To get the latest version, clear the cache and restart your MCP host: `rm -rf ~/.npm/_npx && claude mcp restart socraticode`. Alternatively, use `npx -y socraticode@latest` in your config to always check for updates on startup (slightly slower).\n\n**OpenCode** — add to your `opencode.json` (or `opencode.jsonc`):\n\n```json\n{\n  \"mcp\": {\n    \"socraticode\": {\n      \"type\": \"local\",\n      \"command\": [\"npx\", \"-y\", \"socraticode\"],\n      \"enabled\": true\n    }\n  }\n}\n```\n\n**OpenAI Codex CLI** — add to `~/.codex/config.toml`:\n\n```toml\n[mcp_servers.socraticode]\ncommand = \"npx\"\nargs = [\"-y\", \"socraticode\"]\n```\n\nRestart your host. On first use SocratiCode automatically pulls Docker images, starts its own Qdrant and Ollama containers, and downloads the embedding model — one-time setup, ~5 minutes depending on your connection. After that, it starts in seconds.\n\n**First time on a project** — ask your AI: **\"Index this codebase\"**. Indexing runs in the background; ask **\"What is the codebase index status?\"** to monitor progress. Depending on codebase size and whether you're using GPU-accelerated Ollama or cloud embeddings, first-time indexing can take anywhere from a few seconds to a few minutes (it takes under 10 minutes to first-index +3 million lines of code on a Macbook Pro M4). Once complete it doesn't need to be run again, you can search, explore the dependency graph, and query context artifacts.\n\n**Every time after that** — just use the tools (search, graph, etc.). On server startup SocratiCode automatically detects previously indexed projects, restarts the file watcher, and runs an incremental update to catch any changes made while the server was down. If indexing was interrupted, it resumes automatically from the last checkpoint. You can also explicitly start or restart the watcher with `codebase_watch { action: \"start\" }`.\n\n> **macOS / Windows on large codebases**: Docker containers can't use the GPU. For medium-to-large repos, [install native Ollama](https://ollama.com/download) (auto-detected, no config change needed) for Metal/CUDA acceleration, or use [OpenAI embeddings](#openai-embeddings) for speed without a local install. [Full details.](#embedding-performance-on-macos--windows)\n\n> **Recommended**: For best results, add the [Agent Instructions](#agent-instructions) to your AI assistant's system prompt or project instructions file (`CLAUDE.md`, `AGENTS.md`, etc.). The key principle — **search before reading** — helps your AI use SocratiCode's tools effectively and avoid unnecessary file reads.\n\n> **Claude Code users**: If you installed the SocratiCode plugin, the Agent Instructions are included automatically as skills — no need to add them to your `CLAUDE.md`. The plugin also bundles the MCP server, so you don't need a separate `claude mcp add`.\n\n> **Advanced**: cloud embeddings (OpenAI / Google), external Qdrant, remote Ollama, native Ollama, and dozens of tuning optio","github_created_at":"2026-02-26T16:12:26+00:00","created_at":"2026-07-07T17:43:59.695664+00:00","updated_at":"2026-08-21T06:02:20.443472+00:00","categories":[{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"ai-assistant","name":"ai-assistant"},{"slug":"ast","name":"ast"},{"slug":"claude-code","name":"claude-code"},{"slug":"code-graph","name":"code-graph"},{"slug":"context-engine","name":"context-engine"},{"slug":"embeddings","name":"embeddings"},{"slug":"gemini-cli-extension","name":"gemini-cli-extension"},{"slug":"mcp","name":"mcp"}],"trust":{"provenance":{"is_fork":false,"github_id":1167732163,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-21T06:02:19.389Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":12,"days_since_push":6,"last_release_at":"2026-08-14T17:23:06Z","stars_delta_30d":131,"open_issues_delta_30d":5},"security_summary":{"status":"no_manifest","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:24:47.909Z","medium_count":0,"scan_profile":"mcp_manifest","critical_count":0}},"capability_facts":{"mcp":{"source":"package.json:@modelcontextprotocol/*","observed_at":"2026-08-21T06:02:19.847Z","server_manifest":true},"scan":{"source":"repo_scan","observed_at":"2026-08-21T06:02:19.847Z"},"deploy":{"source":"dockerfile:docker-compose.yml","self_host":true,"observed_at":"2026-08-21T06:02:19.847Z","managed_saas":false},"has_cli":{"value":true,"source":"package.json:bin|scripts","observed_at":"2026-08-21T06:02:19.847Z"},"languages":{"value":["typescript","javascript"],"source":"github.language+package.json","observed_at":"2026-08-21T06:02:19.847Z"},"has_docker":{"value":true,"source":"dockerfile:docker-compose.yml","observed_at":"2026-08-21T06:02:19.847Z"},"license_spdx":{"value":"AGPL-3.0","source":"github.license","observed_at":"2026-08-21T06:02:19.847Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["- When working with extremely large codebases (>40 million lines of code), as SocratiCode supports such scale efficiently.","- For teams that prioritize local and private setups over cloud-based services, ensuring data privacy and compliance.","- In scenarios where zero-setup deployments are preferred for quick integration into existing environments.","- When integrating with AI frameworks like Claude or Gemini is desired to enhance development workflows."],"when_not_to_use":["- If your project scale is small (<1 million lines of code), you may find SocratiCode's capabilities overkill and more complex than necessary.","- For organizations that do not require local setup and can leverage cloud-based solutions, as using SocratiCode might offer redundant features."],"source":"enrich:decision_facts","observed_at":"2026-07-12T11:28:42.146Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"SocratiCode is an advanced code intelligence tool tailored for large-scale enterprise projects."}]}}