What is an MCP server and why it needs secure secrets management

TLDR

MCP servers connect AI agents to real infrastructure, which makes them powerful and credential-heavy. When secrets are hardcoded in config files or stored in long-lived sessions, they become prime targets for token leakage, data exfiltration, and full-environment compromise. The fix is not more sanitization scripts. It is centralized, runtime-based secrets management with short-lived credentials, strict scoping, rotation, and built-in auditability from the start.

Understanding MCP servers

Model Context Protocol (MCP) is an open standard that enables AI applications to securely connect to external data sources and tools. You can think of an MCP server as an integration layers that sit between Large Language Models and the services they need to access, translating AI requests into backend operations.

In the MCP architecture, there are three core components: MCP clients that run inside AI agents and make requests, MCP servers that act as integration layers, exposing tools and actions, and third-party services such as GitHub, databases, or cloud APIs that the MCP servers connect to. The server wraps these external systems and translates incoming protocol calls into backend logic your AI agent can use.

MCP servers enable AI applications to perform concrete actions, such as querying databases, reading files, managing cloud resources, and interacting with SaaS platforms via natural language. This makes building complex workflows on top of LLMs more scalable, but it also creates a significant security surface that depends entirely on how credentials are managed.

Why MCP servers are credential-intensive

MCP servers function as intermediaries that must authenticate to multiple backend systems simultaneously. A single MCP deployment might require credentials for databases, cloud-provider APIs, internal services, and third-party SaaS platforms. This credential aggregation is necessary for the server to fulfill its role, but it also makes MCP configurations a high-value target.

Each tool or resource exposed by the MCP server requires authentication to the underlying service. For example, an MCP server providing GitHub integration needs a personal access token, while one connecting to a database requires connection strings and passwords. When you configure an MCP server, you're essentially granting it the keys to your entire infrastructure in a single configuration file.

The challenge intensifies because MCP enables long-lived sessions and stateful agents with context persistence. So unlike traditional API integrations, where credentials are used for discrete, short-lived operations, MCP credentials can persist in context memory, creating an entirely new category of exposure: contextual secret leakage, where the protocol layer itself becomes an unintentional secret repository (yay).

The security risk of improper secrets management

Research analyzing thousands of MCP servers reveals systematic failures in credential management. Approximately 48% of reviewed MCP servers recommend storing sensitive credentials in plaintext files such as .env or JSON configuration files. Neither approach is secure, as both aggregate multiple secrets into a single file, making it a prime target for automated attacks.

The most common misconfigurations include data source credentials such as API keys, database passwords, and service tokens, which are hardcoded directly in server configuration files. When MCP servers are bound to network interfaces without proper authentication, all clients connecting to the server inherit the same privileged access with no user-specific authorization or access control mechanisms.

Security researchers discovered 492 MCP servers running without any client authentication or traffic encryption, collectively providing access to 1,402 MCP tools, with more than 90% providing direct read access to their data sources. This means anyone who gains access to an exposed MCP server can exfiltrate private information using natural language without needing to know how to code.

Specific attack vectors

Improper secrets management in MCP systems creates multiple exploitable vulnerabilities. Hardcoded credentials become long-lived secrets that cannot be easily updated or changed, and if compromised, they can be used indefinitely. Credentials might leak from configuration files, environment variables, source code, or even process memory after a vulnerability is successfully exploited.

Token mismanagement represents one of the most severe risks in MCP-based systems. Developers frequently embed tokens in configuration files, environment variables, or prompt templates, and because MCP enables long-lived sessions, these tokens can be inadvertently stored, indexed, or retrieved later through user prompts, system recalls, or log inspection. Attackers monitoring shared logs or interacting with the same system context can extract and misuse these credentials to access internal repositories, pipelines, or production APIs.

MCP servers with inadequate restrictions introduce critical risks, including arbitrary code execution with MCP client privileges, data exfiltration through compromised servers, and lateral movement to backend data sources using hardcoded credentials. Man-in-the-middle attacks on unencrypted network traffic between clients and servers can intercept and modify sensitive data, altering tool output and agentic workflows.

The consequences of credential exposure

When MCP credentials are compromised, the impact cascades across your entire infrastructure. Exposure of authentication tokens can lead to complete environment compromise through API or infrastructure access, unauthorized code modifications or repository tampering, and lateral movement across integrated services such as CI/CD pipelines, cloud storage, and issue trackers.

Because MCP-based systems often operate autonomously or on behalf of users, a leaked token can grant high-impact permissions without direct human intervention. The fundamental difference from traditional attacks is that threat actors no longer require extensive technical knowledge. A stolen MCP configuration and natural language query are all they need to exfiltrate sensitive corporate data.

This risk intensifies significantly in cloud production deployments where MCP configurations grant access to critical resources such as cloud account management, databases, and distributed software binaries. With access tokens leaked, threat actors can inject malicious code into software distribution channels, triggering supply chain attacks.

Secure secrets management for MCP servers

Proper secrets management transforms MCP from a security liability into a controlled integration point. The foundational principle is eliminating hardcoded credentials entirely. Instead of embedding API keys in configuration files, load them from environment variables or dedicated secrets management systems at runtime.

Organizations should deploy centralized secrets management platforms that provide secure credential storage, automated rotation, and comprehensive audit trails. Systems like AWS Secrets Manager, or specialized platforms like Doppler, enable MCP servers to retrieve credentials dynamically without ever persisting them to disk. This ensures tokens never appear in logs, core dumps, or version control, and that the LLM never sees the raw credential.

Implement OAuth token delegation patterns in which clients obtain tokens directly from identity providers that represent specific user identities and permissions. Short-lived tokens with automatic refresh capabilities, implemented on the client side using secure token storage such as keychains or credential managers, dramatically reduce the exposure window. The MCP server validates tokens issued by the approved OAuth provider and uses them for downstream API calls, maintaining user context throughout the operation.

Enforce aggressive credential rotation policies combined with immediate revocation capabilities. Schedule rotation jobs or leverage vendor-supplied auto-rotation features, and pipe audit logs to a SIEM so that unauthorized access triggers immediate alerts. This operational hygiene, with no hard-coding, least-privileged access, dynamic credentials, and rigorous logging, preserves user trust and prevents catastrophic data exposure.

Taking action

If you're deploying MCP servers, audit your current configuration immediately. Remove any hardcoded credentials from JSON configuration files and environment variables. Implement secure secret management systems that retrieve credentials from vaults at runtime rather than storing them in plaintext.

For organizations managing multiple MCP deployments, centralized secrets management becomes operationally critical. Platforms like Doppler provide the infrastructure to securely store credentials, automatically rotate them on schedules or on demand, and deliver comprehensive audit trails that satisfy compliance requirements while enabling rapid incident response.

To experience how centralized secrets management transforms MCP security posture, you can create a free Doppler account and implement secure credential management for your MCP servers in under an hour. The platform integrates directly with MCP architectures, eliminating the need for plaintext configuration files while providing the visibility and control necessary to protect your AI infrastructure.