contactscience-mcp

MCP server for Contact Science — an appointment-setting / sales engagement CRM platform. Exposes its appointment and call-block reporting endpoints as MCP tools.

Naming note: MSPbots' own integration is registered as "Contact Science" (subjectCode=SCIENCE); the underlying API host is Contact Science's own backend, www.klpzmedia.com. This MCP covers exactly the 2 GET endpoints MSPbots itself has configured — see Known Gaps below for why the scope stops there.

MSPbots Connector

The MCP Gateway built for MSPs: visible, controlled, and your data stays where it belongs.

Get started at connect.mspbots.ai →

MSPbots Connector gives your AI clients one MCP URL to reach your entire MSP stack (RMM, PSA, documentation, security, finance), and gives you control over who can call which tool and a record of everything that was called.

Hosted service: connect.mspbots.ai · Free to use.

Why Connector

Quick start

1. Sign up at connect.mspbots.ai.

2. Connect your vendors. Pick from 150+ connectors and authorize each one on the vendor's own page, or bring your own API keys. No extra vendor accounts needed.

3. Set access. Create roles and decide which tools each role may call. Nothing is allowed until you allow it.

4. Add your MCP URL to your AI client. Copy the URL from your Connector dashboard into Claude, ChatGPT, Cursor, VS Code, Gemini, Codex, or any MCP-capable client.

5. Ask your AI to do real work, and watch every call appear in the audit log.

Features

Unified gateway

• One MCP URL for all your AI clients

• 150+ connectors across the MSP stack

• Custom MCP servers supported, free

• Authorization happens on each vendor's own page; the AI never sees passwords or tokens

• Bring your own credentials: use the vendor API keys you already have

• Multiple accounts per app; connect once, reuse across AI clients

• Tool search: finds the right action for the task

• One sign-in; vendor credentials are injected behind the scenes and OAuth tokens refresh automatically

Visibility

• Audit log for every tool call (who, which vendor, when)

• Usage dashboard: call volume, top vendors, error rate, per-user activity

• Export audit logs to CSV, or stream to Loki, Graylog, or LogScale (SIEM)

• Optional recording of tool arguments and result summaries (off by default, enabled per organization)

Control

• Per-role, per-tool allowlist, deny by default

• owner / admin / member roles

• SCIM provisioning with Entra ID, Okta, JumpCloud, and Google Workspace

Security

• Credentials encrypted one record at a time (AES-256-GCM, per-record key)

• AI clients authenticate with OAuth 2.1 + PKCE

• Vendor responses are scanned for prompt-injection patterns and returned as structured data. This is one layer of defense, not a guarantee against every attack.

• Static egress IP for customer firewall and API allowlisting

Pricing

Free.

Links: connect.mspbots.ai · mspbots.ai

Related MCP server: mcp-keap

Overview

• Stateless HTTP service. No credentials are ever persisted — each request supplies its own token via a header, used only for the lifetime of that single request.

• Supports concurrent requests; per-request credential isolation is done via Python contextvars, not a global/shared client instance.

• Entry points: POST /mcp (MCP protocol) and GET /health (health check).

• Default port: 8080 (configurable via MCP_HTTP_PORT).

Authentication

Contact Science authenticates with a single static API token, generated in the Contact Science admin portal. MSPbots' own integration convention sends this token as the raw value of the authorization header — no Bearer prefix — and this server forwards it exactly that way.

HEADER authentication parameters

Missing the header returns 401:

{
  "error": "Missing credentials",
  "message": "This server requires the X-ContactScience-Authorization header",
  "required_headers": ["X-ContactScience-Authorization"],
  "optional_headers": []
}

Important quirk: unlike most REST APIs, Contact Science's own endpoints return HTTP 200 even when the token is invalid — the error is embedded in the JSON body instead ({"error": "Unauthorized", "message": "Invalid API Key"}). This server's client (api_client.py) detects that body shape and raises a tool-level error regardless of the HTTP status code, so callers still see a structured error envelope (see Error Handling below) rather than silently getting an error payload back as if it were real data.

Error Handling

Tool errors are returned as a structured JSON envelope (never raised as protocol-level exceptions), so a calling agent can branch on code and retryable programmatically:

{"error": {"code": "unauthorized", "message": "Invalid API Key", "retryable": false}}

code is one of a fixed vocabulary: not_configured, unauthorized, not_found, invalid_argument, rate_limited, upstream_error.

Environment Variables

MCP Endpoint

• POST /mcp — MCP protocol (streamable HTTP transport)

• GET /health — health check, returns {"status": "ok"} (local probe only, does not depend on the upstream Contact Science API)

Tool List

Both tools are plain GET calls against the same 2 endpoints MSPbots itself calls. start_date is required — confirmed by live testing, this is not documented anywhere and contradicts MSPbots' own stored integration config (which shows empty params); calling either endpoint without it returns {"error": "Invalid parameters", "message": "startDate parameter is missing"}. end_date is an accepted optional filter. Each tool also accepts an optional extra_params pass-through dict for any further query-string filters, since Contact Science does not publish a public API reference (see Known Gaps).

Test Example

# Health check
curl -s http://localhost:8080/health

# Call a tool via the MCP protocol (streamable HTTP) — requires an
# initialize handshake first per the MCP spec; abbreviated example below
# shows the tool-call request body only:
curl -s -X POST http://localhost:8080/mcp \
  -H "X-ContactScience-Authorization: <your-contact-science-token>" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "mcp-session-id: <session-id-from-initialize>" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
      "name": "contactscience_get_appointments",
      "arguments": {"start_date": "2026-01-01"}
    }
  }'

Expected: 200 with the appointments list on a valid token; 200 with {"error": "Unauthorized", "message": "Invalid API Key"} in the body on an invalid token — surfaced by this server as a tool-level structured error envelope (see Error Handling above), not treated as real data.

Live-verified (2026-07-29) against a real Tech Guardian tenant token: both contactscience_get_appointments and contactscience_get_call_block returned real data end-to-end through this running server.

API Reference

• No public API documentation exists for Contact Science's reporting API. The vendor's marketing site (contactscience.com) and backend (klpzmedia.com) do not publish a developer reference, and no Swagger/OpenAPI spec or third-party reference was found. The two endpoints implemented here were confirmed directly from MSPbots' own stored integration configuration and by probing the live API.

Known Gaps

• Scope is exactly MSPbots' 2 configured endpoints, not a larger vendor API surface — Contact Science does not publish any public API reference, so (like bvoip-mcp earlier in this program) there was no broader public spec to weigh a wider scope against.

• Response field shapes are not independently documented — whatever the live API returns is passed through as-is; no schema/field reference exists to validate against.

• Beyond start_date/end_date, further filter parameters are undocumented; extra_params is provided so a caller who discovers additional supported filters can still pass them through.

• start_date being required could not be discovered from any documentation or from MSPbots' own stored config (which shows it calling both endpoints with zero params) — it was only found by calling the live API and reading the resulting error message. MSPbots' own sync may be relying on a default/fallback behavior not visible from the stored config, or may be passing it through a mechanism this investigation didn't surface.