Ranked, with the criteria stated up front.

The best LLM proxies for AI coding agents, ranked

Ranked specifically for one job: sitting in front of coding agents on a developer's own machine. A tool that's excellent for a shared team gateway can still rank lower here if that isn't what it's built for.

Transparent local proxy setups ranked by install friction

The axis here is narrow and I want it stated before any ranking happens: how much work stands between installing a tool and having every coding agent CLI on the machine routed through it. One certificate installed once, with no per-tool base URL rewrite and no environment variable per agent, scores highest. Anything that asks you to point Claude Code at one endpoint, then Codex at the same endpoint, then Cursor, then repeat after every update, scores lower. This says nothing about which tool has the best dashboard, the widest provider catalog, or the best team story. Several tools below beat Probe0 badly on those. They lose on this one because they were built to sit behind an SDK, not in front of a whole machine.

Exact-match caching tools that stay entirely on local disk, ranked

One axis only: when an identical request comes back, does the cache answer it from a file on the machine that made the request, with zero packets leaving that machine? Not "is the cache fast", not "is it self-hostable", not "does it do semantic matching". Tools rank high here when the hit path is disk. They rank low when the hit path is a hosted edge, a Redis you still have to reach, or when the product simply is not a response cache at all. Several tools near the bottom of this list are better products than the ones above them on every other axis I care about.

AI dev tools ranked by how upfront they are about their limits

One axis only: does the tool tell you what it does not do, on the page where you decide whether to install it. Platform support, how far it scales, and which providers or tools it actually covers. Nothing here is a ranking of quality, speed, or how much money the thing saves you. Several products near the bottom of this list are larger, older, and better funded than the ones near the top. They rank low because their front pages describe a much wider scope than their docs support, and you only find the edges after you have wired something up.

Cost tools built for a solo developer, not a team gateway, ranked

The axis here is narrow and I want it stated before any ranking happens: how well does the tool serve one developer, running coding agents on their own machine, who wants to spend less without standing up infrastructure. Not throughput. Not governance. Not how many providers are in the catalog. A tool ranks high if a single person can install it in an evening, keep their traffic local, and see real numbers afterwards. A tool ranks low on this axis if its shape assumes an org behind it, even when that shape is excellent for the org. Several of the tools near the bottom of this list are better engineered than the ones near the top. They are built for a different buyer.

Local-only AI coding agent proxies, ranked

The axis here is narrow on purpose: does the tool run entirely on the machine in front of you, with no vendor server ever seeing your requests, and does it actually sit in front of coding agent CLIs like Claude Code, Codex, or Cursor. A lot of the names below are excellent products that fail that second test because they are gateways meant to be deployed once and shared by a team, which means a server, which means the axis excludes them by design, not by insult. Local model runners rank near the top even though most of them are not proxies at all, because they satisfy the on-device half of the claim more completely than anything that touches a network.

Local-to-cloud auto-retry routers, ranked

One axis here, and it is narrow on purpose: when a model running on your own machine returns an answer that is not good enough, does the tool escalate to a cloud model on its own, inside the same request, without you re-running the prompt? Almost everything in this space does failure-triggered fallback, which fires when the local endpoint errors or times out. That is a different and much easier problem than a local model that answers confidently and badly. Tools are ranked by how close they get to the harder version, and a tool that has no local-model path at all cannot place high no matter how good its cloud failover is.

macOS-native local proxies for AI coding agents, ranked

The axis here is narrow on purpose: was this thing built to sit on one macOS developer machine and intercept traffic from Claude Code, Codex, and Cursor locally, or is it a server-shaped gateway that happens to run on a Mac because Docker runs on a Mac. Those are different products solving different problems. A gateway meant for a team's production traffic across ten cloud regions is not wrong for not being a menubar app. But if what you want is one proxy, one certificate, and every coding agent CLI on your laptop routed through it with no server to operate, that's a much smaller list than the general LLM gateway category suggests.

Tools where every feature reports exactly what it saved you, ranked

The axis here is narrow and I want it stated before any ranking happens: can you switch one cost-saving feature off, and does that feature tell you, on its own, what it saved you? A tool that shows a single monthly spend number scores badly even if it saves a lot, because you cannot tell which part earned its keep. A tool that says caching saved this much, routing saved this much, and the cheap-model tier saved this much, each attributable and each separately switchable, scores well. Everything below is judged on that and nothing else. A tool can be excellent at observability, at team governance, or at raw provider breadth and still sit low here, because those are different axes with different winners.

AI proxy tools ranked by setup time to first saved dollar

The axis here is narrow on purpose: how long it takes one developer, on one laptop, to go from install to a number that says money was saved on coding agent traffic. Not feature count, not provider coverage, not enterprise readiness. Setup work counts, account creation counts, and a tool that only shows you what you spent scores lower than one that also reduces it. If you are deploying a gateway for a team of forty, this is the wrong ranking to read and I say so below.

Tools that work across Claude Code, Codex, and Cursor at once, ranked

The axis here is narrow on purpose: point Claude Code, Codex, and Cursor at one thing, configure it once, and be done. Not "supports many providers" (most of these do). Not "has a dashboard" (most of these do too). The question is whether a single local setup actually intercepts every coding agent CLI running on your machine, or whether you are editing three different config files and three different API base URLs to get there. Most of the field was built for a different problem, teams routing server-side traffic through a hosted gateway, so they rank lower here even though they are good at what they were built for.

Tools that tell you which process actually made the expensive call, ranked

One axis here, stated up front so you can disagree with it before you read the list. When a call costs more than you expected, can the tool tell you which process on your machine made it, without you having modified that process? Not which model. Not which API key. Which running program. Almost every tool below can give you a per-model total, and several give you far richer traces than I do once you instrument your own code. But the agent CLIs on my laptop are not my code. Claude Code, Codex and Cursor do not tag their outbound calls with anything I chose, so any tool whose attribution depends on headers or SDK spans I inject is going to lose on this specific axis and win on others.

Tools that tell you if you're overpaying for your subscription tier, ranked

The axis for this ranking is narrow on purpose: does the tool measure your real usage and then say, in words, that you are paying for a tier above what you use? Not "does it have a cost dashboard". Not "does it show a spend graph". A dashboard that renders a number and leaves the conclusion to you scores lower than a tool that draws the conclusion. Almost every product in the LLM cost category is built to help a company govern API spend across teams, which is a different problem from a single developer with a Claude Max or Cursor or Codex subscription wondering whether the cheaper plan would have covered last month. I rank against the second problem, because that is the one I built for.

Tools that collapse duplicate simultaneous LLM calls, ranked

One axis only: when two or more identical requests are in flight at the same moment, does the tool hold the duplicates and serve them all from a single upstream response? That is a narrow question, and it is not the same as caching. A normal cache can only help after the first response has finished writing. Parallel subagents do not wait politely for that; four of them fan out inside the same second with the same system prompt and the same file context, and a read-after-write cache misses all four. Everything below is ranked by how it behaves in that specific window, on one developer machine, with coding-agent traffic. Tools that are excellent at other things and irrelevant to this one are ranked low here and say so.

Semantic caching tools ranked by tool-call safety

One axis only: when a request carries tool calls or tool results, does the cache layer refuse to serve a similarity match? A near-miss on a plain prose question costs you a slightly stale answer. A near-miss on a turn that contains a tool_use block hands the agent someone else file path, someone else diff, someone else shell command, and the run keeps going as if nothing happened. So this list ranks by refusal, not by hit rate. Tools that ship no similarity matching at all score well here by not having the failure mode, and I say so where that is what is happening rather than pretending they solved something.

Tools with a real hard spend cap (not just a dashboard), ranked

One axis here, stated before I rank anything: when a coding agent crosses a per-run or per-day dollar cap, does the tool sit in the request path and stop the next call, or does it show you a number after the money is gone? Enforcement scores. Alerting does not. A second, smaller factor breaks ties: how much work it takes to get that enforcement in front of Claude Code, Codex and Cursor on one developer machine. Tools built for team platforms score fine on enforcement and lose points only on that setup axis, which is a fair trade to name out loud rather than hide.

Caching tools that never touch the network, ranked

One axis here, and it is narrow on purpose: when a repeated request gets answered from cache, does anything leave the machine? Storage on local disk or a local vector index scores high. A cache that lives at a vendor edge, or that only works because your traffic already goes through someone else's endpoint, scores low no matter how good it is at the caching part. Plenty of excellent tools land in the lower tiers because they were never trying to be local, and I say so in each note.