How do I get my CompanyCam Access Token?

In the CompanyCam web app, go to **Your Company > Account > Access Tokens** and generate a new token. Copy it and paste it below.

What is a project in CompanyCam?

A project is a container for a specific jobsite where you store photos, documents, and comments related to that location.

Can I upload photos with this integration?

The current version focuses on browsing and retrieving project data and photos. Photo uploading may be added in future updates.

CompanyCam MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: CompanyCam
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to CompanyCam through Vinkius, pass the Edge URL in the `mcps` parameter and every CompanyCam tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="CompanyCam Specialist",
    goal="Help users interact with CompanyCam effectively",
    backstory=(
        "You are an expert at leveraging CompanyCam tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in CompanyCam "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About CompanyCam MCP Server

Connect your AI assistant to CompanyCam, the photo-first documentation platform built for contractors and field service teams.

When paired with CrewAI, CompanyCam becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call CompanyCam tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Project Browsing — List and search projects by name, address, or status to find jobsite records quickly.
Photo Management — Retrieve photos for any project, view timestamps and GPS coordinates, and check annotations.
Team Overview — Check current user info, roles, and company account details.

The CompanyCam MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect CompanyCam to CrewAI via MCP

Follow these steps to integrate the CompanyCam MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from CompanyCam

Why Use CrewAI with the CompanyCam MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with CompanyCam through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

CompanyCam + CrewAI Use Cases

Practical scenarios where CrewAI combined with the CompanyCam MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries CompanyCam for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries CompanyCam, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain CompanyCam tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries CompanyCam against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

CompanyCam MCP Tools for CrewAI (10)

These 10 tools become available when you connect CompanyCam to CrewAI via MCP:

create_project

Create a new project in CompanyCam

get_current_user

Retrieve details of the authenticated user

get_photo_details

Retrieve details of a specific photo

get_project

Retrieve detailed information about a specific project

list_all_photos

Retrieve a list of photos across all projects in the company

list_project_documents

Retrieve a list of documents attached to a project

list_project_photos

Retrieve all photos associated with a specific project

list_projects

Retrieve a list of projects from CompanyCam

list_users

Retrieve a list of all users in your company

search_projects

Quickly find a project by name

Example Prompts for CompanyCam in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with CompanyCam immediately.

"Show me the first 20 projects in CompanyCam."

"List all photos for project 'proj-xxxx'."

"Create a new project at '456 Maple Drive'."

Troubleshooting CompanyCam MCP Server with CrewAI

Common issues when connecting CompanyCam to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

CompanyCam + CrewAI FAQ

Common questions about integrating CompanyCam MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.