MCP Connector Evaluation Template

Evaluating Model Context Protocol (MCP) connectors for your portfolio or client base requires looking beyond features. A systematic approach is necessary to assess deployment models, security controls, data access rights, and total cost, especially when managing multiple, distinct systems. This guide provides a structured template to compare options and select connectors that are secure, scalable, and fit for the unique needs of advisory and investment firms.

The business problem: Choosing the right MCP connectors for your firm

As AI assistants become integrated into professional workflows, the need to connect them securely to live business data grows. For private equity firms, M&A advisors, and fractional CFOs, this challenge is multiplied across a diverse portfolio or client list. Each company may use a different CRM, ERP, or finance application. Choosing the wrong MCP connector can introduce security risks, create unexpected costs, reinforce data silos, or fail to deliver the needed functionality.

The goal is to standardize evaluation criteria to make informed decisions. A consistent process helps you compare official vendor-supplied connectors (like those for Salesforce or HubSpot) with community-built or custom solutions. It ensures that any tool you deploy meets your firm's standards for security, governance, and operational efficiency, regardless of the underlying business application.

Illustrative example: An advisory firm evaluates CRM connectors

A fractional CFO firm wants to use an AI assistant to streamline client reporting. Their goal is to ask natural language questions about sales pipelines, accounts receivable aging, and budget variances for three of their clients.

• Client A uses HubSpot CRM.
• Client B uses Salesforce Enterprise Edition.
• Client C uses a legacy, on-premise industry-specific ERP.

The firm uses the evaluation template below to compare their options. They assess the official, vendor-hosted MCPs from HubSpot and Salesforce against a potential custom-built connector for the legacy ERP.

• Deployment: The HubSpot and Salesforce connectors are hosted by the vendors, requiring minimal setup. The custom connector for the ERP would need to be self-hosted on a cloud server, adding infrastructure and maintenance overhead.
• Access: They note that the HubSpot MCP has read-only restrictions on certain data objects, while the Salesforce MCP offers broader read/write capabilities, all governed by user permissions.
• Cost: The official connectors have a predictable per-user or usage-based cost. The self-hosted option involves development, hosting, and ongoing maintenance costs, which are harder to predict.

This structured comparison helps the firm adopt a hybrid strategy: use the official connectors for Clients A and B for immediate value and security, while scoping a phased, read-only custom build for Client C's most critical data.

MCP connector evaluation template

Use this worksheet to compare MCP connectors for a specific system (e.g., CRM, ERP) across different vendors or deployment models. This helps ensure a consistent, apples-to-apples comparison for your portfolio or client base.

Prerequisites and limitations

Before deploying an MCP connector, ensure you have the necessary foundations in place.

Prerequisites:

• AI Assistant: Your firm must use an AI model and interface (e.g., Claude) that supports the Model Context Protocol.
• System Compatibility: The source application (e.g., NetSuite, Salesforce) must be on a version and edition that is compatible with the chosen connector. Check current vendor documentation.
• User Permissions: You need an account in the source system with sufficient permissions to authorize the connection via a mechanism like OAuth. The AI's access will be limited by the permissions of the authorizing user.

Limitations:

• Access, Not Extraction: MCP provides governed, real-time access for specific tasks. It is not an ETL (Extract, Transform, Load) tool for bulk data migration or a replacement for a data warehouse.
• Tool-Based Functionality: An AI assistant can only perform actions that are explicitly defined as `tools` by the MCP connector. It cannot perform arbitrary database queries or access unauthorized parts of the application.
• No Transfer of Rights: Using MCP to access business data does not grant you, your firm, or the AI model any new rights to that data. It does not confer ownership, rights to train AI models, or permission to license or sell the data. For more information, see our guide on MCP and data licensing rights.

Questions to ask your software provider or implementation team

When engaging with vendors or developers, use these questions to clarify critical details.

1. Is your MCP connector generally available (GA) or in a beta/preview state?
2. What are the specific prerequisites for our software version and license tier?
3. Is the connector hosted by you, or does it require self-hosting? What are the infrastructure and maintenance requirements for a self-hosted deployment?
4. What authentication methods do you support, such as OAuth 2.0 or SSO? How are user permissions from the source system inherited and enforced?
5. Can you provide a complete list of supported `tools`, clearly distinguishing between read-only and write-enabled actions?
6. What is your pricing model? Is it based on users, API calls, a flat subscription, or a combination?
7. What level of audit logging is available to track AI agent activity and data access?
8. Does the use of this MCP connector count against our platform's standard API rate limits?

Next step with SourceX

The process of evaluating MCP connectors gives you a clear inventory of the systems and data your clients or portfolio companies rely on. Once you understand the internal value of connecting this data to your own AI tools, the next logical question is whether that data has external value.

SourceX helps established US operating companies license their valuable, non-public operational data to enterprise AI labs and data buyers. As a referral partner, you can introduce companies that may be a good fit. SourceX manages the evaluation, contracting, and technical integration, ensuring the supplier company's data rights are protected throughout the process. The process is permission-based and requires explicit authorization from the company's decision-makers.

For private equity firms and advisors managing multiple companies, our Portfolio Data Opportunity Scanner can help screen for potential data licensing opportunities. For successful introductions where a buyer licenses the data, partners receive 25% of the platform fees SourceX collects, up to $100,000 per referred company.

Sources

• Lovable Agent integrations (Current docs)
• Chronograph MCP launch (October 28 2025)
• Affinity private-capital MCP (Updated July 16 2026)
• AlphaSense MCP overview (Current beta docs)
• PitchBook data in Claude (October 28 2025)
• HubSpot remote MCP GA (April 13 2026)
• Attio MCP (Current vendor page)
• Salesforce hosted MCP GA (April 2026)
• Slack MCP new tools (May 13 2026)
• Snowflake managed MCP (Current vendor docs)

Vendor capabilities change. Check current official documentation before relying on any product detail.