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Mcp Server For Bitrix24

# mcp-bitrix24 MCP server for Bitrix24 Tasks, Workgroups, and Users. Implements MCP/JSON-RPC over STDIO. ## Features - Tasks: create, update, close, reopen, list - Workgroups: create, list - Users: list, current user, available fields - Task fields: available fields + validation for `create_task.fields` ## Requirements - Node.js >= 18 - Bitrix24 webhook URL ## Install / Build ```bash npm install npm run build ``` Run via npm: ```bash npx mcp-bitrix24 ``` ## Configuration Set the Bitrix24 webhook URL via environment variable: ``` BITRIX24_WEBHOOK_URL=https://<your-domain>/rest/<user_id>/<webhook>/ ``` Example Codex MCP config: ```toml [mcp_servers.bitrix24] command = "npx" args = ["-y", "mcp-bitrix24"] [mcp_servers.bitrix24.env] BITRIX24_WEBHOOK_URL = "https://<your-domain>/rest/<user_id>/<webhook>/" ``` ## Tools ### Tasks - `create_task` - Input: `title` (string, required), `description?` (string), `responsible_id?` (number), `group_id?` (number), `fields?` (object) - Output: `{ task_id: number }` - Note: if `fields` is provided, keys are validated against `get_task_fields`. - `update_task` - Input: `task_id` (number, required) + at least one of: `title?`, `description?`, `responsible_id?`, `group_id?` - Output: `{ task_id: number }` - `close_task` - Input: `task_id` (number, required) - Output: `{ task_id: number }` - `reopen_task` - Input: `task_id` (number, required) - Output: `{ task_id: number }` - `list_tasks` - Input: `responsible_id?` (number), `group_id?` (number), `start?` (number), `limit?` (number) - Output: `{ tasks: [{ id, title, status }] }` - `get_task_fields` - Input: `{}` - Output: `{ fields: { [field: string]: object } }` - `list_task_history` - Input: `task_id` (number, required), `filter?` (object), `order?` (object) - Output: `{ list: [ { id, createdDate, field, value, user } ] }` ### Workgroups - `create_group` - Input: `name` (string, required), `description?` (string) - Output: `{ group_id: number }` - `list_groups` - Input: `limit?` (number) - Output: `{ groups: [{ id, name }] }` ### Users - `list_users` - Input: - `filter?` (object) - `sort?` (string) - `order?` ("ASC" | "DESC") - `admin_mode?` (boolean) - `start?` (number) - `limit?` (number) - Output: `{ users: [{ id, name, last_name, email?, active }] }` - Note: `filter` supports Bitrix24 `user.get` filters (including prefixes like `>=`, `%`, `@`, etc.). `start` controls paging (Bitrix returns 50 records per page); `limit` is a local slice after the API response. - `get_user_fields` - Input: `{}` - Output: `{ fields: { [field: string]: string } }` - `get_current_user` - Input: `{}` - Output: `{ user: { id, name, last_name, email?, active } }` ## Architecture Clean architecture layers: - `mcp/` โ€” protocol, transport, server - `adapters/` โ€” MCP tools mapping to domain - `domain/` โ€” entities, services, ports - `infrastructure/` โ€” Bitrix24 REST client ## Development Notes - Input validation uses `zod`. - Transport: STDIO only. - Build: `tsc` (`npm run build`). ## Contributing See `CONTRIBUTING.md` for guidelines.

Mcp Server Rabel

Project description ๐Ÿง  RABEL MCP Server Recidive Active Brain Environment Layer Local-first AI memory with semantic search, graph relations, and soft pipelines. Mem0 inspired, HumoticaOS evolved. By Jasper & Root AI from HumoticaOS ๐Ÿ’™ ๐Ÿš€ Quick Start # Install pip install mcp-server-rabel # For full features (vector search) pip install mcp-server-rabel[full] # Add to Claude CLI claude mcp add rabel -- python -m mcp_server_rabel # Verify claude mcp list # rabel: โœ“ Connected ๐Ÿค” What is RABEL? RABEL gives AI assistants persistent memory that works 100% locally. Before RABEL: AI: "Who is Storm?" โ†’ "I don't know, you haven't told me" After RABEL: You: "Remember: Storm is Jasper's 7-year-old son" AI: *saves to RABEL* Later... You: "Who is Storm?" AI: *searches RABEL* โ†’ "Storm is Jasper's 7-year-old son!" No cloud. No API keys. No data leaving your machine. ๐Ÿ› ๏ธ Available Tools Tool Description rabel_hello Test if RABEL is working rabel_add_memory Add a memory (fact, experience, knowledge) rabel_search Semantic search through memories rabel_add_relation Add graph relation (A --rel--> B) rabel_get_relations Query the knowledge graph rabel_get_guidance Get soft pipeline hints (EN/NL) rabel_next_step What should I do next? rabel_stats Memory statistics ๐Ÿ“– Examples Adding Memories # Remember facts rabel_add_memory(content="Jasper is the founder of HumoticaOS", scope="user") rabel_add_memory(content="TIBET handles trust and provenance", scope="team") rabel_add_memory(content="Always validate input before processing", scope="agent") Searching Memories # Semantic search - ask questions naturally rabel_search(query="Who founded HumoticaOS?") # โ†’ Returns: "Jasper is the founder of HumoticaOS" rabel_search(query="What handles trust?") # โ†’ Returns: "TIBET handles trust and provenance" Knowledge Graph # Add relations rabel_add_relation(subject="Jasper", predicate="father_of", object="Storm") rabel_add_relation(subject="TIBET", predicate="part_of", object="HumoticaOS") rabel_add_relation(subject="RABEL", predicate="part_of", object="HumoticaOS") # Query relations rabel_get_relations(subject="Jasper") # โ†’ Jasper --father_of--> Storm rabel_get_relations(predicate="part_of") # โ†’ TIBET --part_of--> HumoticaOS # โ†’ RABEL --part_of--> HumoticaOS Soft Pipelines (Bilingual!) # Get guidance in English rabel_get_guidance(intent="solve_puzzle", lang="en") # โ†’ "Puzzle: Read โ†’ Analyze โ†’ Attempt โ†’ Verify โ†’ Document" # Get guidance in Dutch rabel_get_guidance(intent="solve_puzzle", lang="nl") # โ†’ "Puzzel: Lezen โ†’ Analyseren โ†’ Proberen โ†’ Verifiรซren โ†’ Documenteren" # What's next? rabel_next_step(intent="solve_puzzle", completed=["read", "analyze"]) # โ†’ Suggested next step: "attempt" ๐Ÿ—๏ธ Architecture โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ RABEL โ”‚ โ”‚ Recidive Active Brain Environment Layer โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚ โ”‚ โ”‚ Memory Layer โ†’ Semantic facts with embeddings โ”‚ โ”‚ Graph Layer โ†’ Relations between entities โ”‚ โ”‚ Soft Pipelines โ†’ Guidance without enforcement (EN/NL) โ”‚ โ”‚ โ”‚ โ”‚ Storage: SQLite + sqlite-vec (optional) โ”‚ โ”‚ Embeddings: Ollama nomic-embed-text (optional) โ”‚ โ”‚ โ”‚ โ”‚ 100% LOCAL - Zero cloud dependencies โ”‚ โ”‚ โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ Graceful Degradation RABEL works with minimal dependencies: Feature Without extras With [full] Text memories โœ… โœ… Text search โœ… (LIKE query) โœ… (semantic) Graph relations โœ… โœ… Soft pipelines โœ… โœ… Vector search โŒ โœ… Embeddings โŒ โœ… (Ollama) ๐ŸŒ Philosophy "LOKAAL EERST - het systeem MOET werken zonder internet" (LOCAL FIRST - the system MUST work without internet) RABEL is built on the belief that: Your data stays yours - No cloud, no tracking, no API keys Soft guidance beats hard rules - Pipelines suggest, not enforce Bilingual by default - Dutch & English, more coming Graceful degradation - Works with minimal deps, better with more ๐Ÿ™ Credits Inspired by: Mem0 - Thank you for the architecture insights! We took their ideas and made them: 100% local-first Bilingual (EN/NL) With soft pipelines With graph relations ๐Ÿข Part of HumoticaOS RABEL is part of a larger ecosystem: Package Purpose Status mcp-server-tibet Trust & Provenance โœ… Available mcp-server-rabel Memory & Knowledge โœ… Available mcp-server-betti Complexity Management ๐Ÿ”œ Coming ๐Ÿ“ž Contact HumoticaOS Website: humotica.com GitHub: github.com/jaspertvdm ๐Ÿ“œ License MIT License - One love, one fAmIly ๐Ÿ’™ Built with love in Den Dolder, Netherlands By Jasper & Root AI - December 2025