Financial Services firms trust Stacklok’s AI agent guardrails
Put AI agents into production without compromising security, compliance, or accountability
Solve financial services-specific challenges to optimizing use of AI agents
Stacklok’s Model Context Protocol (MCP) Platform is built for regulated environments, so you can move from experimentation to production.
Security by Design
Enforce least privilege for AI agents with authorization, network isolation, and secure token exchange. AI agents only interact with the systems and data you explicitly allow.
Compliance and auditability
Integrate with your existing observability stack (Datadog, Splunk, etc.) to generate a complete record of AI tool usage. Every action is traceable, reviewable and defensible.
Operational simplicity
Provide developers and knowledge workers with a single, controlled endpoint to access the exact tool(s) an AI agent is permitted to use. Eliminate bespoke integrations.
Apply MCP to high-impact financial services use cases
Accelerate your existing AI initiatives and integrate with your current AI stack
Developer productivity
Embed internal data into developer workflows without over-privileging AI systems. Connect IDEs like Cursor or Claude Code to your identity provider (Okta, Entra, etc.) and observability solution.
Fraud Detection
Improve precision by enabling AI agents to correlate signals across multiple internal systems while keeping all access
Process automation
Trust your agents with asynchronous decisions and actions by establishing clear and secure guardrails. Establish accountability for every automated workflow.
The State of MCP in Financial Services 2026
We surveyed 100 technical leaders at financial services enterprises to explore their Model Context Protocol progress and priorities. Find out where you stand relative to your peers. Full study results are available with no forms to fill out.
Differentiated value for financial services firms
Leaders trust our MCP platform because we:
Run in your VPC
Most MCP solutions are SaaS, which is a non-starter for financial services. Stacklok runs in your Virtual Private Cloud, so your data stays in your environment.
Built on open source
Stacklok builds in the open, with the community. Our popular ToolHive platform can solve many of your MCP challenges immediately, and ensures a sustainable path forward.
Offer a full platform
Start by curating your own MCP registry or implementing a custom MCP gateway, and then expand to the complete Stacklok MCP platform according to your timeline and need.
Take the next steps
Continue with your due diligence and know that we’re always available for an open conversation
for Enterprise
Start by curating a registry of trusted MCP servers for your enterprise
for Individuals
Dive into the ToolHive repo and docs, and then engage directly with our team.
Frequently asked questions
Stacklok’s Enterprise Model Context Protocol Platform is designed for regulated industries like financial services.
Stacklok’s Model Context Protocol Platform helps financial services firms securely control how AI models access tools, data, and workflows. It provides a standardized, auditable way to define what context an AI system is allowed to use, under what conditions, and with what safeguards. This allows banks, insurers, and asset managers to deploy AI safely without exposing sensitive systems or data.
Financial services organizations operate in highly regulated environments where data access, decision traceability, and operational controls are critical. Model Context Protocol enables firms to constrain AI behavior by design, limiting which systems an AI can interact with and how. This reduces risk while still allowing teams to innovate with AI-powered workflows.
Traditional AI governance and MLOps platforms focus on model training, monitoring, or lifecycle management. Stacklok focuses on runtime control of AI context: what an AI can see and do in production. This is especially important for financial services use cases involving real systems, real data, and real risk.
The platform enables organizations to define explicit rules governing AI access to tools and data, creating clear accountability and traceability. This makes it easier to demonstrate control over AI-driven actions during audits and compliance reviews. Stacklok’s design aligns with the expectations of regulated financial environments.
Yes. Stacklok is model-agnostic and designed to work alongside existing LLMs, IDEs, and internal systems. It provides a consistent control layer regardless of which models or vendors a firm uses, helping teams avoid lock-in while maintaining security. This is further reinforced by Stacklok’s work in the community and the company’s popular open source ToolHive MCP platform.