A collection of autonomous agent examples demonstrating how to integrate the **Neonia Model Context Protocol (MCP) Gateway** using the official
A collection of autonomous agent examples demonstrating how to integrate the Neonia Model Context Protocol (MCP) Gateway using the official Streamable HTTP transport standard. That is what the agent mcp examples mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
This repository will continuously grow with new patterns demonstrating deterministic, high-performance AI agents.
The server publishes 2 tools. What each one is for:
Directories — python/langgraph/zero-bloat-jq-filter, python/langgraph/chained-json-jq-filter, python/langgraph/auto-discovery-url-to-markdownSetup — uv sync && uv run python agent.pyInstallation goes through your MCP client rather than a global install: point it at tsx on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
Configuration is passed through the environment: NEONIA_API_KEY, OPENROUTER_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
To run these examples, you will need: 1. A Neonia API Key (NEONIA_API_KEY) 2. An OpenRouter API Key (OPENROUTER_API_KEY) Configure these in the .env file within the specific example directory you wish to run.
Plenty of knowledge and memory servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Agent MCP Examples's toolset — Directories, Setup — is a fair guide to whether it matches your workflow. It is maintained by neonia-io; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| Directories | python/langgraph/zero-bloat-jq-filter, python/langgraph/chained-json-jq-filter, python/langgraph/auto-discovery-url-to-markdown, python/langgraph/stateful-cloud-memory, python/langgraph/persistent-knowledge-memory |
| Setup | uv sync && uv run python agent.py |
{
"mcpServers": {
"agent-mcp-examples": {
"command": "npx",
"args": ["-y", "tsx"],
"env": {
"NEONIA_API_KEY": "your-value",
"OPENROUTER_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
To run these examples, you will need: 1. A Neonia API Key (NEONIA_API_KEY) 2. An OpenRouter API Key (OPENROUTER_API_KEY) Configure these in the .env file within the specific example directory you wish to run.
| Variable | Description | Required |
|---|---|---|
| NEONIA_API_KEY | Credential the server authenticates with. | Yes |
| OPENROUTER_API_KEY | Credential the server authenticates with. | Yes |
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.