mcp-daktela

Read-only MCP server for the Daktela contact center REST API v6. Gives any MCP-compatible LLM client (Claude, Cursor, etc.) full read access to tickets, calls, emails, chats, contacts, CRM records, campaigns, and real-time agent status.

Why

A contact center generates thousands of interactions daily — calls, emails, chats across multiple channels. The raw data is all in Daktela, but extracting insight from it requires either manual review or custom reporting. This server bridges Daktela to an LLM, letting you run analysis that would be impractical to do by hand:

Email quality audit — "Analyze all emails from the last 72 hours. Flag any interactions with negative customer sentiment, lost deals where the customer chose a competitor, or unprofessional agent tone. For each flagged email, show metadata, a link to the ticket, and a description of the issue."

Call transcript analysis — "Review call transcripts from the last week. Identify calls where the customer escalated, the agent struggled with product knowledge, or a commitment was made but not followed up. Summarize each with the agent name, customer, and recommended action."

Sales pipeline review — "Look at all open sales tickets in S1-Discovery and S2-Qualification stages. For each lead, read the latest email thread and assess whether the deal is progressing, stalled, or at risk. Rank by MRR and recommend which ones need attention this week."

The LLM reads the actual conversation content — email bodies, chat messages, call transcripts — and applies judgment that no dashboard or filter can replicate.

Tools

40 read-only tools organized by domain:

Category	Tools
Tickets	list_tickets, count_tickets, get_ticket, get_ticket_detail, list_account_tickets, list_ticket_categories
Activities	list_activities, get_activity
Calls	list_calls, get_call, get_call_transcript, list_call_transcripts
Emails	list_emails, get_email
Messaging	list_web_chats, get_web_chat, list_sms_chats, get_sms, list_messenger_chats, get_messenger_chat, list_instagram_chats, get_instagram_chat, list_whatsapp_chats, get_whatsapp_chat, list_viber_chats, get_viber_chat
Contacts & CRM	list_contacts, get_contact, list_accounts, get_account, list_crm_records
Campaigns	list_campaign_records, list_campaign_types
Reference data	list_queues, list_users, list_groups, list_pauses, list_statuses, list_templates
Real-time	list_realtime_sessions

All list tools support pagination (skip, take), sorting, and contextual filters (stage, priority, date range, user, queue, etc.). The server includes detailed instructions metadata that teaches the LLM how to use filters, resolve entity names, and navigate relationships between tickets, contacts, and accounts.

Getting started

Prerequisites

• Python 3.12+
• A Daktela instance with a user account that has API access
• uv (recommended) or pip

Install

git clone https://github.com/hajekd/mcp-daktela.git
cd mcp-daktela
uv venv && uv pip install -e ".[dev]"

Run locally with Claude Desktop

Set your Daktela credentials and point Claude Desktop at the server:

{
  "mcpServers": {
    "daktela": {
      "command": "python",
      "args": ["-m", "mcp_daktela"],
      "env": {
        "DAKTELA_URL": "https://your-instance.daktela.com",
        "DAKTELA_USERNAME": "your-username",
        "DAKTELA_PASSWORD": "your-password"
      }
    }
  }
}

That's it. The server authenticates against your Daktela instance using the same credentials you use to log in. You can also use DAKTELA_ACCESS_TOKEN instead of username/password if you have a static API token.

Deploy as HTTP server

For shared or remote deployments (e.g., Cloud Run), the server runs in streamable-http mode where each client passes credentials via HTTP headers:

gcloud run deploy mcp-daktela \
  --source . \
  --region europe-west1 \
  --allow-unauthenticated \
  --memory 1Gi

The server also includes a built-in OAuth 2.0 provider for use as a remote MCP server on Claude.ai.

Architecture

src/mcp_daktela/
├── server.py              MCP tool definitions (40 tools)
├── formatting.py          Format API records into readable markdown
├── client.py              Async HTTP client for Daktela REST API
├── filters.py             Build query parameters (filter/sort/pagination)
├── oauth.py               OAuth 2.0 provider for Claude.ai remote MCP
├── auth.py                Per-request credential middleware
├── config.py              Credential resolution (ContextVar → env vars)
├── cache.py               In-process TTL cache for reference data
├── logging_middleware.py   Structured JSON logging for tool calls
└── __main__.py            Entry point

Configuration

Environment variable	Default	Description
DAKTELA_URL	—	Daktela instance URL
DAKTELA_USERNAME	—	Daktela username
DAKTELA_PASSWORD	—	Daktela password
DAKTELA_ACCESS_TOKEN	—	Static API token (alternative to username/password)
MCP_TRANSPORT	stdio	Transport: stdio or streamable-http
PORT	8080	HTTP port (streamable-http mode)
CACHE_ENABLED	true	Enable reference data cache
CACHE_TTL_SECONDS	3600	Cache TTL in seconds

Development

# Unit tests (333 tests, ~1s)
.venv/bin/python -m pytest

# Lint
.venv/bin/python -m ruff check src/ tests/

Integration tests run every tool against a live Daktela instance via the deployed server:

.venv/bin/python scripts/integration_test.py \
  --url https://your-instance.daktela.com \
  --username your-user \
  --password your-password

License

MIT