Alternatives
Products that do what mcp-recorder – VCR.py for MCP servers. Record, replay, verify does
Hi HN, I'm Vlad. I've been building MCP servers and related tooling for a while now, and I kept hitting a class of bug that no unit test caught: someone on the team renames a tool parameter or tweaks a tool description, all the tests pass, but the AI agent that was calling that tool silently breaks. This happens because the model reads tool descriptions and parameter schemas to decide which tool to call and how, so a renamed parameter or a reworded description isn't just a cosmetic change — it directly affects the model's behavior. The MCP spec doesn't have tool versioning available yet, and…
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I noticed the growing security concerns around MCP (https://news.ycombinator.com/item?id=43600192) and built an open source tool that can detect several patterns of tool poisoning attacks, exfiltration channels and cross-origin manipulations. MCP-Shield scans your installed servers (Cursor, Claude Desktop, etc.) and shows what each tool is trying to do at the instruction level, beyond just the API surface. It catches hidden instructions that try to read sensitive files, shadow other tools' behavior, or exfiltrate data. Example of what it detects: - Hidden instructions…
2025 · github.com
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Hi HN, I've been building MCPSpec, an open-source CLI for MCP server reliability. Record sessions, generate mock servers, catch Tool Poisoning, and fail your CI build when something's wrong — without writing test code. There are ways to validate MCP servers today — the MCP Inspector, ad-hoc SDK scripts, unit tests for server internals — but nothing that handles regression detection, security auditing, mock generation, and CI pass/fail checks in one tool. MCPSpec does that: 1. Record a session against your real server, replay it after changes to catch regressions 2. Generate a standalone…
Feb 2026 · light-handle.github.io
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Hi HN! We kept seeing devs get pwned through MCP tools in ways that security scanners completely miss. So we built an open-source analyzer to catch these attacks. Our first OSS by Mighty team. The problem: At Defcon, we saw MCP exploits with 100% success rate against Claude and Llama. Three attack patterns: Hidden Unicode in "error messages" - Paste a colleague's error into Claude, your SSH keys get exfiltrated Trusted tool updates - That database tool you've used for months? Last week's update added credential theft Tool redefinition - Malicious tool redefines "deploy to prod" to run…
2025 · github.com
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Hi! After learning about MCP, I'm really excited about the future of provider-agnostic, re-usable tooling. Unfortunately I've found that while it's easy to implement an MCP server for use with tools that support it (such as Claude Desktop), it's not as easy to implement your own support (such as integrating an MCP server into your own LLM application). We implemented a thin MCP wrapper that easily integrates with Mirascope calls so that you can hook up an MCP server and client super easily to any supported LLM provider. Excited to see what people build with this!
2025 · mirascope.com
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Recently I was trying to use an MCP server to pull data from a service, but hit a limitation: the MCP didn't expose the data I needed, even though the service's REST API supported it. So I wrote a quick CLI wrapper around the API. Worked great, except Claude Code had no structured way to know what my CLI does or how to call it. For `gh` or `curl` the model can learn from the extensive training data, but for a tool I just wrote, it was stabbing in the dark. MCP solves this discovery problem, but it does it by rebuilding tool interaction from scratch: server processes, JSON-RPC transport,…
Feb 2026 · github.com
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Large Language Models (LLMs) are powerful, but they’re limited by fixed context windows and outdated knowledge. What if your AI could access live search, structured data extraction, OCR, and more—all through a standardized interface? We built the JigsawStack MCP Server, an open-source implementation of the Model Context Protocol (MCP) that lets any AI model call external tools effortlessly. Here’s what it unlocks: - Web Search & Scraping: Fetch live information and extract structured data from web pages. - OCR & Structured Data Extraction: Process images, receipts, invoices, and handwritten…
2025
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Hi HN! We’re Theodore and Louis, founders of Armature (YC P26). We reconstruct the entire session behind the MCP tool calls you receive, including what the user asked their agent to do and what the agent thought. You wrap your MCP in 3 lines of code (our SDK is available in Typescript, Python and Go) and start seeing in your dashboard: - All sessions reconstructed: it’s like reading the real conversation the user had inside Claude or ChatGPT! - A ranking of your MCP most popular use cases, built from sessions clustering - The most frequent issues your users’ agents encounter so you can fix…
Aug 2026 · armature.tech
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https://github.com/mcp-shark/mcp-shark Site: https://mcpshark.sh/ I built MCPShark, a traffic inspector for the Model Context Protocol (MCP). It sits between your editor/LLM client and MCP servers so you can: • See all MCP traffic (requests, responses, tools, resources) in one place • Debug sessions when tools don’t behave as expected • Optionally run “Smart Scan” checks to flag risky tools / configs
Dec 2025
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Most of the MCP servers that I’ve seen are tools implemented in standalone projects. To onboard more tools (especially agents and multi-agent workflows) to MCP, I’ve been thinking it’s important to allow AI engineers to continue to prototype in their existing agent frameworks and deploy with minimal conversion when ready. We created the automcp library, which you can add as a dependency to existing projects (CrewAI, LangGraph, Llama Index, OpenAI Agents SDK, Pydantic AI, mcp-agent currently supported but more coming soon). You just need to run a CLI command to create a run_mcp.py file, make…
2025 · github.com
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2025 · github.com
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We’re open-sourcing a simple way to add “canary tools” to AI agents via MCP honeypots. These are functions your agent should never call during normal operation. If a canary is invoked, you get a high-fidelity signal of prompt-injection, tool hijacking, or lateralization—no heuristics, no extra model calls. What it is: - Go framework exposing decoy tools over MCP that look legitimate (names/params/descriptions), return safe dummy output, and emit telemetry when invoked. - Runs alongside your real tools; ship events to stdout/webhook or your pipeline (Prometheus/Grafana,…
Sep 2025
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Stop your coding agent from guessing at datasheets
Jun 2026 · docs.byteask.ai
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Hey HN, Gal, Nir and Doron here. Over the past 2 years, we've helped teams debug everything from prompt issues to production outages. We kept running into the same problem: Jumping between our IDEs and our observability dashboards. So, we built an open-source MCP server that connects any OpenTelemetry backend (Grafana, Jaeger, Datadog, Dynatrace, Traceloop) to our dev environment using an MCP. While there are many MCP servers built for specific providers (like Datadog’s - https://docs.datadoghq.com/bits_ai/mcp_server), they’re closed source (so we can’t easily extend…
Nov 2025 · github.com
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I built Polymcp, a framework that allows you to transform any Python function into an MCP (Model Context Protocol) tool ready to be used by AI agents. No rewriting, no complex integrations. Examples Simple function: from polymcp.polymcp_toolkit import expose_tools_http def add(a: int, b: int) -> int: """Add two numbers""" return a + b app = expose_tools_http([add], title="Math Tools") Run with: uvicorn server_mcp:app --reload Now add is exposed via MCP and can be called directly by AI agents. API function: import requests from polymcp.polymcp_toolkit import expose_tools_http def…
Jan 2026
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