What does pre-execution governance mean for AI agents?

It means validating and approving tool calls before they actually run, letting you enforce policies like blocking dangerous operations, rate-limiting, or parameter validation. This prevents agents from executing unintended or harmful actions.

How do I install and run promptspeak?

Install via npm with `npx @chrbailey/promptspeak-mcp-server@0.4.1`. It runs over stdio transport, so you connect it to your MCP client to intercept and validate tool calls in real time.

Can I use promptspeak with any AI agent framework?

Promptspeak is an MCP server, so it works with any MCP-compatible client or agent framework. Check the registry for supported transports and integration examples.

What kinds of validation rules can I define?

The registry indicates it validates tool calls, but specific rule types and schema details aren't documented in the available metadata. Refer to the project repository or documentation for the full validation rule API.

Is there a performance cost to pre-execution validation?

All validation happens before tool execution, so there's a latency trade-off. For latency-sensitive agents, test with your expected call volume to ensure governance overhead is acceptable.

MCP ServerSTDIOOfficialv0.4.1

PromptSpeak Governance MCP Server

Validate and govern AI agent tool calls before execution. For developers building agentic systems who need safety guardrails and pre-execution policy enforcement.

io.github.chrbailey/promptspeak

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Hosted URL

Local install

Transport

STDIO

Auth

No auth required

What the PromptSpeak Governance MCP server does

How models use it and what it is built for.

Validate and govern AI agent tool calls before execution. For developers building agentic systems who need safety guardrails and pre-execution policy enforcement.

Connect to PromptSpeak Governance

Local install — runs as a subprocess.

npx @chrbailey/promptspeak-mcp-server@0.4.1

Resources

Where to find authoritative docs and source for PromptSpeak Governance.

Source repository

Example prompts for PromptSpeak Governance

Paste any of these into Agent Studio after connecting PromptSpeak Governance.

Set up a validation rule that blocks database delete operations
Configure governance policies for API calls to external services
Show me how to whitelist specific tool parameters before execution
What validation schemas does promptspeak support for tool governance

PromptSpeak Governance MCP server — FAQ

Common questions about connecting and running PromptSpeak Governance.

What does pre-execution governance mean for AI agents?
It means validating and approving tool calls before they actually run, letting you enforce policies like blocking dangerous operations, rate-limiting, or parameter validation. This prevents agents from executing unintended or harmful actions.
How do I install and run promptspeak?
Install via npm with `npx @chrbailey/promptspeak-mcp-server@0.4.1`. It runs over stdio transport, so you connect it to your MCP client to intercept and validate tool calls in real time.
Can I use promptspeak with any AI agent framework?
Promptspeak is an MCP server, so it works with any MCP-compatible client or agent framework. Check the registry for supported transports and integration examples.
What kinds of validation rules can I define?
The registry indicates it validates tool calls, but specific rule types and schema details aren't documented in the available metadata. Refer to the project repository or documentation for the full validation rule API.
Is there a performance cost to pre-execution validation?
All validation happens before tool execution, so there's a latency trade-off. For latency-sensitive agents, test with your expected call volume to ensure governance overhead is acceptable.

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