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MCP Mesh – one endpoint for all your MCP servers (OSS self-hosted)

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MCP Mesh – one endpoint for all your MCP servers (OSS self-hosted)

Hey HN! I’m Gui from deco (decocms.com). We’ve been using this tool internally as the foundation for a few customer AI platforms, and today we’re open-sourcing it as MCP Mesh. MCP is quickly becoming the standard for agentic systems, but… once you go past a couple servers it turns into the same problems for every team: - M×N config sprawl (every client wired to every server, each with its own JSON + ports + retries) - Token + tool bloat (dumping tool definitions into every prompt doesn’t scale) - Credentials + blast radius (tokens scattered across clients, hard to audit, hard to revoke) - No single place to debug (latency, errors, “what tool did it call, with what params?”) MCP Mesh sits between MCP clients and MCP servers and collapses that mess into one production endpoint you can actually operate. What it does: - One endpoint for Cursor / Claude / VS Code / custom agents → all MCP traffic routes through the mesh - RBAC + policies + audit trails at the control plane (multi-tenant org/workspace/project scoping) - Full observability with OpenTelemetry (traces, errors, latency, cost attribution) - Runtime strategies as “gateways” to deal with tool bloat: Full-context (small toolsets), Smart selection (narrow toolset before execution), Code execution (load tools on-demand / run code in a sandbox) - Token vault + OAuth support, proxying remote servers without spraying secrets into every client - MCP Apps + Bindings so apps can target capability contracts and you can swap MCP providers without rewriting everything A small but surprisingly useful thing: the UI shows every call, input/output, who ran it, and lets you replay calls. This ended up being our “Wireshark for MCP” during real workflows. It’s open-source + self-hosted (run locally with SQLite; Postgres or Supabase for prod). You can start with `npx @decocms/mesh` or clone + run with Bun. We’d love your feedback! Links below: Repo: https://github.com/decocms/mesh Landing: https://www.decocms.com/mcp-mesh Blog post: https://www.decocms.com/blog/post/mcp-mesh edit: layout

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, cursor · Missing: mac, macos, model
94%94% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: apps, way, para · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host, calls · Missing: plus, intuitive, reviews
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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