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Tool Governance

Tools in MCP systems are dynamic: they can appear, change capabilities, or disappear without warning through the list_tools call. This dynamism, while powerful for productivity, creates governance challenges that enterprises must address to maintain security, performance, and compliance.

Dynamic Tool Management​

Tools Change Underneath You​

Unlike traditional APIs with fixed endpoints, MCP servers can modify their tool offerings at runtime. A server might offer five tools on Monday and seven tools on Tuesday, including new capabilities like "drop_table" or "execute_raw_sql" that appeared without administrator knowledge or consent.

Remote servers can introduce new capabilities through parameter changes as well. A file management tool might start with restricted access to temporary directories but later expand to access the entire filesystem with additional actions like execution permissions.

Capability Expansion​

Tools can gain new powers without explicit updates. Version changes might expand file operations from read-only to read-write-execute, database queries from SELECT to full database modification capabilities, or API integrations from internal systems to external services.

This gradual expansion of capabilities can increase security risk as tools gain access to critical systems beyond their original scope.

Enterprise Implications​

Security Implications​

Uncontrolled tool proliferation creates multiple risks. Each new tool represents potential attack surface. Tools might bypass existing access controls or provide new vectors for data exfiltration. Without governance, malicious tools can integrate seamlessly alongside legitimate ones.

Every tool addition creates new vulnerabilities. New tools can provide capabilities that circumvent existing restrictions or access and export sensitive information without oversight.

Performance Degradation​

Tool count directly impacts AI effectiveness. Research shows performance drops as tools increase, with large tool spaces reducing performance by up to 85% for some models. OpenAI recommends fewer than 20 tools for optimal accuracy, though they allow up to 128 tools.

Most MCP servers contain four or fewer tools, but outliers exist: the largest cataloged server adds 256 tools, while popular servers like GitHub MCP include 91 tools. Context window limitations further constrain performance as tool descriptions consume available tokens.

Operational Overhead​

Each tool requires security review, documentation, user training, monitoring and maintenance, and incident response procedures. This overhead multiplies with tool count, creating unsustainable operational burden without proper governance.

Tool Classification and Risk Assessment​

MCP Tool Classification​

MCP defines three core primitives for tool organization: Tools (model-controlled functions that AI can invoke), Resources (app-controlled data sources), and Prompts (user-controlled interaction templates).

Read-only tools generally pose lower risk but can still expose sensitive data, reveal system architecture, leak business intelligence, or access confidential information.

Modifying tools require strict governance due to data loss risk, system stability threats, reputation damage potential, and complete system compromise possibilities.

Tool Lifecycle Management​

Discovery and Registration​

Track when new tools appear and implement approval procedures that require authorization before production access. Maintain comprehensive tool inventories with risk analysis.

Tool Controls​

Control tool availability for specific roles and use cases through enable/disable settings, environment restrictions, and user group assignments. Tool customization allows overriding tool names and descriptions to align with enterprise requirements.