AgentRPC
Connect to any function, any language, across network boundaries using [AgentRPC](https://www.agentrpc.com/).
⚡Config Installation
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"agentrpc": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-agentrpc"
]
}
}
}* Note: Requires restart of Claude Desktop app.
Deployment Infrastructure
Adoption Framework for AgentRPC
Before installing any skill, define a clear objective and measurable outcome. A useful implementation question is: what workflow becomes faster, safer, or more reliable after this skill is active? If that answer is vague, delay rollout and tighten scope first.
For most teams, a low-risk pattern is preview-first rollout with one owner, one test scenario, and one rollback plan. Capture failures in a structured log so quality decisions are evidence-based. This is especially important for skills that touch file systems, external APIs, or automation chains with downstream side effects.
- Define success metrics before installation.
- Validate permission scope against policy boundaries.
- Run one controlled pilot and document failure categories.
- Promote only after acceptance checks pass consistently.
Pre-Deployment Review Questions
Use these questions before enabling the skill in shared environments. They reduce surprise incidents and make approval decisions consistent across teams.
- What data can this skill read, write, or transmit by default?
- Which failures are recoverable automatically and which require manual stop?
- Do we have verifiable logs that prove safe behavior under load?
- Is rollback tested, documented, and assigned to a clear owner?
If any answer is unclear, keep rollout in preview and close the gap before production use.
Editorial Review Snapshot
This listing includes an editorial QA layer in addition to automated rendering. Review status is based on documentation depth, content uniqueness, and operational safety signals from the upstream repository.
- Last scan date: 2026-01-18
- README depth: 396 words
- Content diversity score: 0.68 (higher is better)
- Template signal count: 0
- Index status: Quality review hold (noindex)
Recommendation: Keep this skill in review mode. Add a richer implementation guide and concrete failure-mode evidence before requesting broader index coverage.
This page remains accessible to users, but it is excluded from search indexing until editorial enrichment is complete.
Skill Implementation Board
Actionable utility module for rollout decisions. Use the inputs below to choose a deployment path, then execute the checklist and record an output note.
Input: Security Grade
B
Input: Findings
0
Input: README Depth
396 words
Input: Index State
Hold
| Decision Trigger | Action | Expected Output |
|---|---|---|
| Input: risk band moderate, docs thin, findings 0 | Run a preview pilot with fixed ownership and observability checkpoints. | Pilot can start with rollback checklist attached. |
| Input: page is on index hold | Keep rollout internal and add concrete implementation evidence. | Editorial unblock ticket with measurable proof points. |
| Input: context tags/scenarios are missing | Define two concrete scenarios before broad rollout. | Clear scope definition before further deployment. |
Execution Steps
- Capture objective, owner, and rollback contact.
- Run one preview pilot with fixed test scenario.
- Record warning behavior and recovery evidence.
- Promote only if pilot output matches expected threshold.
Output Template
skill=agentrpc mode=B pilot_result=pass|fail warning_count=0 next_step=rollout|patch|hold
🛡️ Security Analysis
Clean Scan Report
Our static analysis engine detected no common vulnerabilities (RCE, API Leaks, Unbounded FS).
DocumentationREADME.md
AgentRPC
Universal RPC layer for AI agents across network boundaries and languages
Overview
AgentRPC allows you to connect to any function, in any language, across network boundaries. It's ideal when you have services deployed in:
- Private VPCs
- Kubernetes clusters
- Multiple cloud environments
AgentRPC wraps your functions in a universal RPC interface, connecting them to a hosted RPC server accessible through open standards:
- Model Context Protocol (MCP)
- OpenAI-compatible tool definitions (OpenAI, Anthropic, LiteLLM, OpenRouter, etc.)
How It Works
- Registration: Use our SDK to register functions and APIs in any language
- Management: The AgentRPC platform (api.agentrpc.com) registers the function and monitors its health
- Access: Receive OpenAPI SDK compatible tool definitions and a hosted MCP server for connecting to compatible agents
Key Features
| Feature | Description |
|---|---|
| Multi-language Support | Connect to tools in TypeScript, Go, Python and .NET (coming soon) |
| Private Network Support | Register functions in private VPCs with no open ports required |
| Long-running Functions | Long polling SDKs allow function calls beyond HTTP timeout limits |
| Full Observability | Comprehensive tracing, metrics, and events for complete visibility |
| Automatic Failover | Intelligent health tracking with automatic failover and retries |
| Framework Compatibility | Out-of-the-box support for MCP and OpenAI SDK compatible agents |
Getting Started
Quick Start
Follow the quick start example on our docs site.
Examples
Explore working examples in the examples directory.
MCP Server
The AgentRPC TypeScript SDK includes an optional MCP (Model Context Protocol) server.
ANGENTRPC_API_SECRET=YOUR_API_SECRET npx agentrpc mcp
This launches an MCP-compliant server for external AI models to interact with your registered tools.
Claude Desktop Integration
Add to your claude_desktop_config.json:
{
"mcpServers": {
"agentrpc": {
"command": "npx",
"args": [
"-y",
"agentrpc",
"mcp"
],
"env": {
"AGENTRPC_API_SECRET": "<YOUR_API_SECRET>"
}
}
}
}
Cursor Integration
Add to your ~/.cursor/mcp.json:
{
"mcpServers": {
"agentrpc": {
"command": "npx",
"args": ["-y", "agentrpc", "mcp"],
"env": {
"AGENTRPC_API_SECRET": "<YOUR_API_SECRET>"
}
}
}
}
License
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
This repository contains all the open-source components and SDKs for AgentRPC.
Related Use Cases
The AgentSkillsHub editorial team evaluates MCP servers, Claude skills, and AI agent integrations for security, reliability, and practical deployment readiness. Every listing undergoes permission audit, README analysis, and operational risk triage before publication.
- Reviewed 450+ MCP server repositories
- Developed security grading methodology (A-F)
- Published agent deployment safety guidelines