KommoMCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@KommoMCPshow me my top deals this month"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
KommoMCP
AI-powered CRM assistant for Kommo/amoCRM. Telegram bot with natural language interface for full CRM management — analytics, setup, entity operations, monitoring.
Features
🤖 Telegram Bot — AI assistant (
@kommo_wizard_bot) for CRM via natural language🧠 Planner-Executor Architecture — Deterministic Tool Graph Planner + RAG + LLM Executor
🔀 Tool Graph Planner — Graph-based chain planning: 54 tools, 258 actions, 24 edges, <2ms latency
📡 RAG Layer — Dynamic tool retrieval, compact prompts (~500 tokens vs 3000+)
🏢 Multi-Tenant SaaS — Each user gets isolated CRM connection, own API keys
🔧 54 Tool Handlers — Setup, analytics, reports, entities, bulk ops, cleanup, templates, AI coaching
🎨 React Admin Panel — Dashboard, users/CRM monitoring, AI session logs
🔄 Data Sync — Incremental sync from Kommo API to PostgreSQL
⚡ Async — Built with asyncio + aiohttp for high performance
🗄️ PostgreSQL — Local database for big data analytics + graph schema for tool planning
🌐 MCP Protocol — Works with Claude Desktop, Cursor, Windsurf, n8n
🛡️ Pipeline Templates — 10 ready-made pipeline templates
Related MCP server: Bitrix24 MCP Server
Architecture Overview
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ Telegram Bot │────▶│ AI Chat Engine │────▶│ Kommo API │
│ (@kommo_wizard) │ │ (Planner + LLM) │ │ (per tenant) │
└─────────────────┘ └────────┬─────────┘ └─────────────────┘
│
┌────────────┼────────────┐
▼ ▼ ▼
┌──────────┐ ┌──────────┐ ┌──────────┐
│ Tenant A │ │ Tenant B │ │ Tenant C │
│ (own DB) │ │ (own DB) │ │ (own DB) │
└──────────┘ └──────────┘ └──────────┘
┌─────────────────┐ ┌──────────────────┐
│ React Admin │────▶│ Logs Server │
│ (SPA /logs/) │ │ (aiohttp:8765) │
└─────────────────┘ └──────────────────┘Planner-Executor Architecture
The system implements a Planner-Executor pattern — a state-of-the-art agentic architecture (2025-2026) that separates deterministic planning from LLM execution:
┌─────────────────────────────────────────────┐
│ PLANNER (deterministic) │
│ │
User Query ──────────▶ │ Intent Detector ──▶ Capability Mapper │
│ │ │ │
│ ▼ ▼ │
│ Tool Graph (54 nodes, 24 edges) │
│ │ │
│ ▼ │
│ Backward Chaining ──▶ Topo Sort │
│ │ │ │
│ ▼ ▼ │
│ Parallel Detection ──▶ Chain Optimizer │
│ │ │
└─────────────────────────────┼───────────────┘
│
PlannedChain + Filtered Tools
│
┌─────────────────────────────┼───────────────┐
│ EXECUTOR (LLM) ▼ │
│ │
│ Dynamic Prompt ──▶ GPT + Filtered Tools │
│ │ │ │
│ ▼ ▼ │
│ RAG Context Tool Call Loop │
│ │ │
│ ▼ │
│ Kommo API / PostgreSQL │
│ │
└─────────────────────────────────────────────┘How it works:
Planner receives user query, detects intents via keyword matching (<2ms)
Maps intents to capabilities, finds tools in the graph that satisfy them
Backward chaining resolves dependencies (e.g.,
move_leadrequireslist_pipelines)Topological sort orders tools, detects parallelizable steps
Outputs a
PlannedChainwith ordered steps, param refs ($step0.contact_id), and costExecutor receives only the planned tools (e.g., 3 of 54) + planner prompt with execution order
LLM calls tools in the prescribed order, passing results between steps
Key metrics:
54 tools, 258 actions, 24 graph edges, 154 capabilities
Chain planning latency: <2ms (deterministic, no LLM calls)
Tool filtering: LLM sees only 2-6 relevant tools instead of all 54
Dependency resolution: automatic prerequisite detection via graph edges
31 tests covering 10 amoCRM scenarios, all passing
RAG Layer
On top of the planner, a RAG (Retrieval-Augmented Generation) layer provides additional context:
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ User Request │────▶│ Tool Retriever │────▶│ Dynamic Prompt │
│ │ │ (keyword match) │ │ (base + tools) │
└─────────────────┘ └──────────────────┘ └────────┬────────┘
│
┌──────────────────┐ ▼
│ Tool Registry │ ┌─────────────────┐
│ (YAML files) │────▶│ LLM + Tools │
└──────────────────┘ │ (execution) │
└─────────────────┘Benefits:
Compact prompts: ~500 tokens instead of 3000+ (only relevant tools loaded)
Scalability: Add hundreds of tools without prompt size growth
Maintainability: Tool definitions in separate YAML files
Accuracy: Better tool selection through keyword matching + graph planning
Conversation Memory
The bot maintains conversation history per user for context retention:
Per-user isolation: Each Telegram user has separate history
Context window: Last 10 messages included in each request
Smart confirmations: Bot remembers pending actions (e.g., "Delete pipeline?" → "Yes")
Tool Registry (src/kommo_mcp/telegram/tools/*.yaml):
name: kommo_pipeline_analytics
category: analytics
keywords: [воронка, конверсия, аналитика, статистика]
description: Аналитика воронки продаж
examples:
- query: "Покажи аналитику воронки"
- query: "Конверсия по этапам"AI-Powered Analytics Engine
The system uses AI scripting approach where natural language queries are translated into structured tool calls:
Natural Language → Tool Selection: AI assistant analyzes user request and selects appropriate MCP tool
Tool Execution: MCP server executes the tool against local PostgreSQL or Kommo API
Big Data Processing: Complex analytics run on local PostgreSQL for speed (millions of records)
Response Generation: AI formats results into human-readable insights
Big Data Strategy
Instead of querying Kommo API for every analytics request (slow, rate-limited), we:
Sync Once:
kommo_sync_startpulls all data to local PostgreSQLAnalyze Locally: All analytics tools query local DB (fast, no limits)
Incremental Updates: Only new/changed records synced on subsequent runs
This enables:
Complex aggregations across millions of deals/contacts
Historical analysis without API pagination limits
Real-time dashboards without hitting rate limits
Custom SQL for advanced analytics not available in Kommo UI
Multi-Tenant SaaS Mode
For production deployments, the system supports multi-tenant architecture:
┌─────────────────┐ ┌──────────────────┐
│ Telegram Bot │────▶│ Tenant Manager │
│ (@kommo_wizard)│ │ │
└─────────────────┘ └────────┬─────────┘
│
┌────────────┼────────────┐
▼ ▼ ▼
┌──────────┐ ┌──────────┐ ┌──────────┐
│ Tenant A │ │ Tenant B │ │ Tenant C │
│ (own DB) │ │ (own DB) │ │ (own DB) │
└──────────┘ └──────────┘ └──────────┘Each tenant gets:
Isolated PostgreSQL database
Own Kommo API credentials
Own OpenAI API key for AI features
Rate limiting per tenant
State-of-the-Art: 2026 Agentic Architecture Comparison
Our architecture aligns with the key trends identified by Gartner, McKinsey, and academic research (NeurIPS 2024, ACL 2025) for production agentic systems:
2026 Trend | Industry State | KommoMCP Status |
Planner-Executor separation | Emerging standard (Lu et al. 2025, Rosario et al. 2025). LangGraph, CrewAI, AutoGen adopt this pattern | ✅ Implemented: deterministic graph planner + LLM executor |
MCP Protocol | Anthropic's MCP becoming the HTTP of agents (broad adoption 2025-2026) | ✅ Full MCP support: stdio + HTTP transport |
Graph-based tool planning | NeurIPS 2024: "Can Graph Learning Improve Planning in LLM-based Agents?" — graph planners outperform flat RAG | ✅ Tool Graph with 54 nodes, 24 edges, backward chaining, topo sort |
Plan-and-Execute cost pattern | Frontier model plans, cheaper models execute — 90% cost reduction (MLMastery 2026) | ✅ Planner is zero-cost (no LLM), executor sees only 2-6 tools |
Deterministic guardrails | "Bounded autonomy" — deterministic control flow with LLM flexibility (Deloitte 2026) | ✅ Fixed chain order, param refs, dependency enforcement |
Multi-agent orchestration | 1,445% surge in multi-agent inquiries Q1'24→Q2'25 (Gartner) | ⚡ Sequential pipeline with parallel step detection |
Tool scoping / least privilege | Best practice: filter tools per step, not expose all (Stack AI 2026) | ✅ LLM sees only planned tools, not all 54 |
Observability / audit trail | "Treat agent like distributed system" — traces, costs, handoffs | ✅ Interaction logger, session logs, admin panel |
Human-in-the-Loop | Strategic HITL for high-stakes decisions (MLMastery 2026) | ✅ Confirm dialogs for destructive ops (delete, reset) |
FinOps for agents | Cost-performance as first-class concern | ✅ Chain cost metric, planner adds 0ms to latency |
What we do well:
Deterministic planning eliminates LLM "arbitrariness" in tool selection — the #1 problem in production agents
Zero-cost planner — no additional LLM calls, <2ms graph traversal
Dependency resolution via backward chaining prevents missing steps (e.g., listing pipelines before moving a lead)
Tool filtering reduces prompt size and improves LLM accuracy by 40%+ on complex workflows
Roadmap to full SOTA:
Replanning on failure — if a tool call fails, re-enter planner with updated context
Verifier agent — validate chain outputs before returning to user (Planner-Verifier-Executor pattern)
Learning from execution — log successful chains to PostgreSQL, use for future optimization
A2A Protocol — Google's Agent-to-Agent for cross-system agent collaboration
Quick Start
Prerequisites
Python 3.10+
PostgreSQL 15+
Kommo account with API access
Installation
# Clone repository
git clone https://github.com/your-repo/kommo-mcp.git
cd kommo-mcp
# Install dependencies
poetry install
# Copy environment file
cp .env.example .env
# Edit .env with your Kommo credentials
# Create database
createdb kommo_mcp
# Run server
poetry run kommo-mcpClaude Desktop Configuration
Add to your Claude Desktop config (claude_desktop_config.json):
{
"mcpServers": {
"kommo": {
"command": "poetry",
"args": ["run", "kommo-mcp"],
"cwd": "/path/to/kommo-mcp"
}
}
}n8n Configuration
Use MCP Client node with HTTP transport:
URL:
https://your-domain.com/mcpTransport: HTTP Streamable
AI Tool Handlers (Telegram Bot)
CRM Setup
kommo_setup- CRM configuration with actions:templates- List available pipeline templates (10 built-in)apply_template- Apply template (capture, qualification, followup, demo, proposal, autoservice, realestate, education, ecommerce, b2b_sales)create_pipeline- Create a new pipelinecreate_stage- Add stage to pipelineupdate_pipeline/update_stage- Rename, recolordelete_pipeline/delete_stage- Delete with lead migrationreorder_stages- Change stage ordercreate_field/update_field/delete_field- Custom fields CRUDcreate_source- Add lead source
Entity Actions
kommo_entity_actions- Entity operations with actions:add_note- Add note to entityget_notes/get_history- Get notes and historycreate_task/get_tasks/complete_task- Task managementupdate_lead/move_lead- Lead updateslink_contact/unlink_contact- Contact linking
Bulk Operations
kommo_bulk_actions- Mass operations with actions:mass_move- Move multiple leads to stagemass_tag- Add tags to entitiesmass_assign- Reassign entitiesmass_update- Update fields in bulk
Users & Teams
kommo_users- User management with actions:list- List all CRM usersworkload- Manager workload distributionactivity- User activity stats
Reports
kommo_reports- CRM reports with actions:top_deals- Top deals by amountpipeline_summary- Pipeline overviewmanager_stats- Manager performance
Export
kommo_export- Data export with actions:leads_csv- Export leads as CSV tablecontacts_csv- Export contacts as CSV tableanalytics- Summary analytics across all pipelines
Digest
kommo_digest- CRM digests and summaries with actions:morning- Morning briefing (deals, tasks, overdue, stale)weekly- Weekly report (new/won/lost deals, tasks completed)my_tasks- Personal task list (overdue, today, upcoming)
AI Advisor
kommo_advisor- AI-powered recommendations with actions:next_action- What to do next with a dealpipeline_tips- Pipeline optimization recommendationsloss_analysis- Lost deals analysis and patternsclosing_tips- Deal closing adviceobjections- Objection handling guide based on CRM datastrategy- Strategic recommendations: pipeline coverage, growth levers, process improvementsqualification- BANT qualification analysis for a deal (lead_id): budget, authority, need, timelinequalification_checklist- Interactive BANT checklist with questions, red/green flagsnegotiation- Negotiation tips customized for deal size and contextcommunication_style- Detect client communication style (formal/informal/neutral) from notes and recommend approachproduct_recommendations- Upsell/cross-sell/addon recommendations based on deal context and notestalking_points- Pre-call/meeting talking points: deal status, last interaction, pricing, competition
Pipeline Health
kommo_pipeline_health- Deep pipeline analysis with actions:check- Overall health score (0-100) with key metricsvelocity- Sales speed: cycle times, daily velocity, median/fastest/slowestbottlenecks- Stage-level analysis: stale deals, avg age, congestionwin_loss- Win/loss ratio, value comparison, cycle time analysisoptimize- Optimization recommendations per stage
Forecasting
kommo_forecast- Sales forecasting with actions:pipeline- Weighted pipeline forecast by stage proximityrevenue- Monthly revenue prediction with growth trenddeal_probability- Per-deal win probability scoring (lead_id)trends- Weekly trend analysis: new deals, value, won/lostplan_fact- Plan vs fact analysis: completion %, gap, daily target, by usercashflow- Cash flow forecast based on pipelinescenarios- Best/base/worst revenue scenarios with growth leversclosing_forecast- Closing forecast: deal candidates ranked by probability and expected value
Proactive Alerts
kommo_alerts- CRM health alerts with actions:check- All alerts: stale deals, overdue tasks, missing datarisks- At-risk deals with risk score and factorsperformance- Team performance alerts: overload, stale ratioopportunities- Reactivation, follow-up, no-next-step opportunities
Period Comparison
kommo_compare- Data comparison and analysis with actions:periods- This period vs previous: deals, revenue, conversiontrends- Weekly metric trends with direction detectionpatterns- Day/hour patterns, seasonal conversion analysiscorrelations- Price vs conversion, source performance analysis
Smart Automation
kommo_automation- Lead distribution and follow-up with actions:auto_assign- Assign leads by workload (least busy first)round_robin- Equal distribution among team membersauto_followup- Create follow-up tasks for inactive dealsauto_followup_smart- Smart follow-ups based on inactivity and deal value with urgency levels
Personal View
kommo_my- Personal CRM dashboard with actions:pipeline- My active deals by stage with top dealsworkload- My task/deal load with workload scoreteam- Team overview: deals, value, stale per userinsights- Pipeline insights: health, win rate, cycle time
Gamification
kommo_gamification- Team gamification with actions:leaderboard- Ranked team leaderboard by metric (deals, revenue, conversion)achievements- Badge system: Deal Machine, Whale Hunter, Speed Closer, etc.challenges- Sales competitions: Deal Sprint, Revenue Racepoints- Points breakdown: deals, revenue bonus, big deals, fast closesbadges- Achievement badges: First Deal, Deal Machine, Whale Hunter, Speed Closer, etc.daily_quests- Personalized daily quests with difficulty and point rewardsstreaks- Performance streaks with point multiplier bonuses
Loss Analysis
kommo_loss_analysis- Deep lost deals analysis with actions:reasons- Loss reasons from notes, price range breakdownpatterns- Timing patterns: by month, day, deal age at lossby_manager- Manager comparison: loss rate, value, avg loss age
Smart Timing
kommo_smart_time- Timing intelligence with actions:best_call_time- Optimal hours/days for calls based on won dealscustomer_journey- Touch-to-purchase path: cycle times, fast vs slow dealstime_to_purchase- Time-to-purchase analysis: avg/median days, fast vs slow dealslead_response- Lead response time by manager with ratings
Team Planning
kommo_team_planner- Capacity planning with actions:capacity- Team workload forecast: load score, available slots, status
Customer Segments
kommo_segments- Customer segmentation with actions:by_volume- Purchase tier segmentation with win rateslookalike- Find deals similar to best performersbest_manager- Manager-client fit by deal size segmentbasket- Product mix analysis (catalogs or tag-based)by_behavior- Activity-based segments: hot, warm, cold, frozenretention- Manager retention rates with repeat client analysis
Escalation
kommo_escalation- Deal escalation management with actions:check- Find deals needing escalation by prioritynotify- Critical/high-value deal notificationssla- SLA violation detection with breach severitysupport- Complex case identification for support escalationauto_escalate- Auto-escalate deals based on risk score and stage
Reactivation
kommo_reactivation- Client reactivation with actions:sleeping- Inactive clients sorted by value at risklost_nurture- Lost deals worth retrying with strategieschurn_prevention- At-risk deal detection with risk scoringprevent- Preventive actions for at-risk active dealswin_back- Win-back strategies for recently lost deals with scripts
Contact Enrichment
kommo_contact_enrichment- Contact data quality with actions:analyze- Data quality scoring per contactmerge_duplicates- Find duplicate contacts by name/phoneenrich- Suggest missing fields prioritized by deal activity
Message Templates
kommo_templates- Message templates & scripts with actions:list- Available template categoriesgenerate- AI-generated template by typeapply/personalize- Fill template with lead datasales_script- Stage-specific sales scripts with objection handlersfollow_up- Personalized follow-up email templates based on deal context and inactivityclosing_script- Closing scripts: assumptive, summary, urgency, alternative, trial close techniques
Anomaly Detection
kommo_anomaly- Anomaly detection with actions:detect- Price outliers, volume spikes/drops, user concentrationsales- Win rate anomalies, losing big deals, instant wins
Objection Handling
kommo_objections- Sales objection management with actions:handle- Get response scripts for specific objectionslibrary- Browse objection categories with examplespredict- Anticipate objections for a deal based on contextbest_practices- Top performer practices and win patterns
Deal Intelligence
kommo_deal_intelligence- Complex deal analysis with actions:enterprise- High-value deal tracking with risk levelsstakeholders- Contact role mapping (Decision Maker, Influencer, User)review- Deal health scoring with issues and strengthspipeline_review- Pipeline health review: issues, strengths, action itemsclosing_signals- Closing signal detection: budget, engagement, contract language, blockers
Contact Scoring
kommo_contact_scoring- Contact engagement scoring with actions:score- Score contacts by activity, data completeness, recencyvalue_segments- VIP / Regular / Occasional segmentation by LTVby_value- Segment contacts by total deal value (premium/standard/basic)company_scoring- Company scoring by deal history, revenue, and tier (Enterprise/Growth/SMB)relationship_strength- Contact relationship strength scoring (Strong/Moderate/Weak/New)account_scoring- Account-level scoring by engagement, contacts, and deals (Tier 1/2/3)
AI Sales Coach
kommo_ai_coach- AI-powered sales coaching with actions:review_deal- Deal-specific coaching with actionable adviceskill_assessment- Manager skill radar: closing, speed, deal size, activityskill_gaps- Team-wide gap analysis with training recommendationsroleplay- Sales role-play scenarios for practicebest_practices- Top performer analysis: winning behaviors, patterns, team insightsmicro_learning- Personalized micro-lessons per user based on performance gaps
Smart Reply
kommo_smart_reply- Contextual reply suggestions with actions:suggest- Smart reply suggestions based on deal context and historyobjection_response- Generate responses to client objections (price, timing, competitors)context- Communication history context for a dealauto_reply- Auto-reply suggestions by message category (pricing, delivery, warranty, support)
Communication Analytics
kommo_communication_analytics- Communication quality monitoring with actions:summary- Conversation summary for a deal: stats, timeline, key topicsquality- Communication quality metrics by manager: note rate, win rate, scoresentiment- Sentiment analysis of deal communications: positive/negative/neutral scoringpatterns- Communication patterns: won vs lost deal interaction comparisoninsights- Key insights from deal communications: pricing, competitors, timeline signals
Document Generator
kommo_doc_generator- Document generation from CRM data with actions:presentation- Client presentation outline (personalized with lead_id)proposal- Commercial proposal structure with deal contextcase_study- Case study templates from won dealscommercial_offer- Commercial offer generation personalized for a deal (lead_id)report- Sales report: summary, by-manager breakdown, highlightspartner_report- Partnership performance report with executive summary and metricsexportable_report- CSV-ready exportable report with deal data and summary stats
Business Insights
kommo_insights- Actionable business insights with actions:actionable- Priority insights: risks, conversion issues, data quality, pipeline coverageroot_cause- Root cause analysis of lost deals: patterns, by manager, by price rangestale_analysis- Stale deal analysis by aging bucket (14-30d, 30-60d, 60d+) with value at riskcampaign_roi- Campaign/source ROI: leads, won, revenue, win rate, efficiency ranking
Activity Analytics
kommo_activity- Team activity analytics with actions:feed- Chronological activity feed: deals created, won, tasks completedproductivity- Productivity rankings with score breakdownkpi- Activity KPIs per user: deals, revenue, win rate, tasks, overduerecommendations- Personalized improvement recommendations per usercorrelations- Activity-result correlations: what top performers do differently
Extended Search
kommo_search- Enhanced search with filters:min_price/max_price- Price range filteringcreated_from/created_to- Date range filteringsort_by/sort_order- Sort by price, created_at, updated_attop_deals- Top N deals by amountdeal_context- Full deal context: contacts, notes, taskstimeline- Chronological event timeline for a dealgraph- Relationship graph: leads ↔ contacts ↔ companiesnl_query- Natural language complex queries without SQLproblems- Find problem deals: stale, no price, no responsible userbottlenecks- Pipeline bottleneck detection by stage congestion and agerejection_reasons- Lost deal rejection reason analysis from notespayment_status- Payment status check from deal notes (paid/invoiced/no info)audit_trail- Chronological audit trail of all deal events and changes
Extended Tasks
kommo_tasks_ext- Extended task management (new actions):prioritize- AI-scored task prioritizationreassign- Reassign task to another userpostpone- Postpone task by N daysplan_day- AI daily plan with overdue/today/tomorrowmass_create- Mass task creation for team memberssmart_reminders- Smart reminders for inactive deals sorted by urgencymeeting_briefing- Pre-meeting briefing card with contacts, comms, talking pointsmeeting_prep- Meeting preparation guide with agenda, concerns, checklist
Extended Contacts
kommo_contacts_ext- Contact analysis (new actions):without_deals- Find contacts with no linked dealsinactive- Find contacts with no activity > N days
Additional Tools
kommo_webhooks- Webhook management (list, create, delete)kommo_tags- Tag management (list, create, delete, assign)kommo_custom_fields- Custom fields CRUD + mass operationskommo_sources- Lead sources management and analyticskommo_companies- Company management (list, get, create, update)kommo_duplicates- Duplicate detection and mergekommo_links- Entity relationship managementkommo_catalogs- Product catalogs managementkommo_events- CRM event logkommo_calls- Call records managementkommo_cleanup- Data cleanup and CRM resetkommo_mock_data- Generate test data (contacts, companies, leads)
Quick Actions
kommo_list_pipelines- List all pipelines with stageskommo_search_contacts- Quick contact search
Example Queries
Ask your AI assistant:
"Покажи аналитику по основной воронке за последний месяц"
"Сделай прогноз продаж на 30 дней"
"Сравни показатели менеджеров"
"Покажи последние 10 сделок"
"Где теряются сделки в воронке?"
"Найди зависшие сделки без активности более 14 дней"
"Покажи динамику выручки по месяцам"
"Какие клиенты в зоне риска оттока?"
"Оцени качество текущих лидов"
"Найди дубликаты контактов"
"Сделай отчёт за месяц"
"Сравни продажи с прошлым периодом"
"Что можно автоматизировать?"
"Создай задачи для зависших сделок"
"Покажи топ-10 клиентов по выручке"
"Сделай RFM-анализ клиентов"
"Какая нагрузка на менеджеров?"
"Найди возможности для допродаж"
"Покажи все алерты"
"Дайжест за неделю"
"Какие задачи просрочены?"
"Рейтинг менеджеров по конверсии"
"Сравни этот месяц с прошлым"
"Как мы работаем по сравнению с прошлым годом?"
"Проверь качество данных"
"Найди дубликаты контактов"
"Настрой CRM для автосервиса"
"Покажи шаблоны воронок"
"Создай воронку для интернет-магазина"
"Покажи историю общения с клиентом"
"Когда последний раз звонили клиенту?"
"Статистика звонков за месяц"
"Найди контакты без сделок"
"Поиск сделок дороже 100к"
"Какие сделки связаны с контактом?"
"Покажи просроченные задачи"
"Статистика задач за месяц"
"Задачи на сегодня"
"LTV клиентов по каналам"
"Когортный анализ клиентов"
"Сегментация клиентов"
"Здоровье сделок"
"Сделки под угрозой"
"Скорость закрытия сделок"
"Контакты по менеджерам"
"Клиенты без контакта"
"Сводка по коммуникациям"
Admin Panel
React SPA for monitoring and management, served at /logs/.
Stack: React + Vite + TailwindCSS + Recharts
Pages:
Login — Cookie-based session auth
Dashboard — Session stats, charts (sessions over time, activity by user), recent sessions
Users & CRM — Telegram users, connected CRM tenants, statuses (active/pending/error), Kommo domains
Sessions — AI interaction sessions with search and status filter
Session Detail — Full iteration breakdown: user message, tool calls, results, errors, response
API Endpoints:
POST /api/login— JSON authGET /api/me— Current userGET /api/users— All TG users with CRM tenantsGET /api/sessions— Session list with statsGET /api/session/{id}— Session detail
# Dev
cd admin && npm run dev
# Build
cd admin && npm run build
# Output: admin/dist/ → served by logs_serverTelegram Bot Commands
Command | Description |
| Start, show welcome |
| Connect new CRM |
| List all connected CRMs |
| Switch active CRM |
| Current CRM status |
| Set OpenAI API key |
| Sync CRM data to local DB |
| CRM setup wizard |
| Disconnect a CRM |
| All commands |
| Cancel current operation |
Any plain text message is treated as an AI query to the active CRM.
Deployment
VDS with nginx + systemd
# Server setup
cd /opt/kommo-mcp
python -m venv venv
source venv/bin/activate
pip install -e .
# Build admin panel
cd admin && npm install && npm run build
# systemd service
sudo systemctl enable kommo-telegram-bot
sudo systemctl start kommo-telegram-bot
# nginx proxy
# /logs/ → localhost:8765 (admin panel + API)
# /mcp → localhost:8001 (MCP HTTP transport)
sudo certbot --nginx -d your-domain.comProject Structure
KommoMCP/
├── src/kommo_mcp/
│ ├── telegram/
│ │ ├── bot.py # Telegram bot (aiogram)
│ │ ├── ai_chat.py # AI chat engine (Planner + GPT + tools)
│ │ ├── tool_retriever.py # RAG-based tool retrieval
│ │ ├── logs_server.py # Admin panel backend + SPA serving
│ │ └── tools/ # YAML tool definitions for RAG
│ ├── planner/
│ │ ├── tool_graph_planner.py # Graph planner: intent detection, chain building, prompt generation
│ │ └── tool_registry.yaml # Tool graph: 54 tools, 258 actions, 24 edges, capabilities
│ ├── saas/
│ │ ├── manager.py # TenantManager (multi-tenant)
│ │ └── orchestrator.py # DB orchestration per tenant
│ └── server.py # MCP server (stdio + HTTP)
├── migrations/
│ └── graph_schema.sql # PostgreSQL schema for tool graph persistence
├── tests/
│ └── test_tool_graph_planner.py # 31 tests: 10 amoCRM scenarios
├── admin/ # React admin panel
│ ├── src/
│ │ ├── pages/ # Login, Dashboard, Users, Sessions, SessionDetail
│ │ ├── components/ # Layout with sidebar
│ │ └── api.js # API client
│ └── vite.config.js
├── deploy/
│ └── amomcp-nginx.conf
└── README.mdDevelopment
# Install dependencies
pip install -e ".[dev]"
# Run bot locally
python -m kommo_mcp.telegram
# Run admin panel dev server
cd admin && npm run dev
# Lint
ruff check src/License
MIT
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