mcp-context-forge vs plano
IBM's registry + proxy federating MCP, A2A and REST/gRPC into one governed endpoint: discovery, auth, rate limits, guardrails, OTel tracing, 40+ plugins — scales to K8s with Redis federation. — versus — AI-native Envoy-based proxy for agentic apps: agent orchestration via a 4B routing model, smart LLM routing, guardrail filter chains and zero-code OTEL traces. Rust, framework-agnostic.
Overlapping ambition, different layer: Plano is an Envoy data plane routing LLM traffic with guardrails; ContextForge is a registry/proxy governing tool and agent endpoints.
| mcp-context-forge | plano | |
|---|---|---|
| Stars | 4.2k | 6.9k |
| Forks | 798 | 476 |
| Language | Python | Rust |
| License | Apache-2.0 | Apache-2.0 |
| Last activity | yesterday | 5 days ago |
| Topics | gateway | gateway, orchestration |
| Curated connections | 2 | 5 |
mcp-context-forge — the curator's take
The enterprise answer for the TOOL plane: where model gateways govern LLM calls, ContextForge governs MCP servers, A2A agents and legacy REST — wrapping the lot as one compliant MCP endpoint with RBAC and tracing. When NOT: a laptop with three MCP servers — this is platform infrastructure (Postgres, Redis, K8s) with real ops weight, and the 0.x release train moves fast enough that upgrades need reading the notes.
plano — the curator's take
Reach for it when multi-agent code is drowning in hidden middleware — intent routing, provider quirks, guardrail hooks, tracing glue. Plano moves all of that out-of-process: agents are plain OpenAI-compatible HTTP servers in any language, orchestration is YAML plus a purpose-built 4B router model. NOT for a quick single-agent demo (it adds an infra hop and Envoy operational surface), and note the catch: the hosted Plano-Orchestrator LLM is free-tier only — production means running the routing models yourself or getting API keys. If you only need provider unification, LiteLLM is lighter.