---
license: mit
language:
  - en
tags:
  - agents
  - llm
  - mcp
  - reliability
  - agent-stack
  - npm
  - pypi
  - typescript
  - python
  - anthropic
  - openai
  - tool-use
library_name: agent-stack
---

# agent-stack

Six small, single-concern reliability libraries for production LLM agents — published independently to **npm**, **PyPI**, and the **Model Context Protocol** registry. Each library is zero-dependency, under 500 LOC, and addresses one specific failure mode that production agent teams have to handle.

## Paper

Backed by a peer-reviewable artifact paper with a DataCite DOI:

- **DOI:** [10.5281/zenodo.20074702](https://doi.org/10.5281/zenodo.20074702)
- **Title:** _Six Reliability Primitives for LLM Agents: An Artifact Pattern for Stackable, Single-Concern Libraries_
- **Status:** Under review at ASE 2026 Tools track.

## The six primitives

| Library | Concern | Failure mode it addresses |
| --- | --- | --- |
| **AgentFit** | Context-window fitting | Token-aware truncation with multiple strategies. Pluggable tokenizers for OpenAI / Anthropic / open models. |
| **AgentGuard** | Network egress allowlisting | Blocks the "agent suddenly POSTs PHI / secrets to attacker.com" failure mode. |
| **AgentSnap** | Snapshot tests for tool-call traces | Catches silent regressions when a model's tool-call shape changes between deploys. |
| **AgentVet** | Tool-arg validation | Throws a `ToolArgError` carrying an LLM-friendly retry hint, so the next turn can self-correct. |
| **AgentCast** | Structured-output validate-and-retry | Bring-your-own-LLM JSON validator + retry loop. |
| **AgentBudget** | Per-run token + dollar caps | Hard cap with hook for early termination. Prevents runaway loops billing $1000 on a single query. |

Each ships in three runtime forms: **TypeScript on npm**, **Python on PyPI**, and an **MCP-server variant** callable from Claude Desktop, Cursor, Continue, or any MCP client.

## Install

### TypeScript (npm)

```bash
npm i @mukundakatta/agentvet @mukundakatta/agentguard @mukundakatta/agentbudget
```

### Python (PyPI)

```bash
pip install agentvet agentguard agentbudget
```

### MCP server (Claude Desktop config)

```json
{
  "mcpServers": {
    "agentvet": { "command": "npx", "args": ["-y", "@mukundakatta/agentvet-mcp"] },
    "agentguard": { "command": "npx", "args": ["-y", "@mukundakatta/agentguard-mcp"] }
  }
}
```

## Source

Umbrella repo: [github.com/MukundaKatta/agent-stack](https://github.com/MukundaKatta/agent-stack)

Per-library repositories (TS + Python + MCP variants) — search GitHub topic [`agent-stack`](https://github.com/search?q=user%3AMukundaKatta+topic%3Aagent-stack) for the full list.

## Why it exists

Reliability concerns for LLM agents are typically bundled into one heavy framework that asks you to adopt prompting, tool routing, and runtime governance as a single dependency. agent-stack inverts that: each concern is a separate library you can adopt à la carte without buying into a programming model.

The artifact paper documents the six primitives, the cross-cutting invariants the design enforces, the trade-offs of single-concern packaging, and the operational questions that emerge when reliability is split across many small dependencies.

## Citation

```bibtex
@misc{katta2026agentstack,
  author       = {Katta, Mukunda Rao},
  title        = {Six Reliability Primitives for LLM Agents:
                  An Artifact Pattern for Stackable, Single-Concern Libraries},
  year         = {2026},
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.20074702},
  url          = {https://doi.org/10.5281/zenodo.20074702}
}
```

## License

MIT.