PostHog MCP Leaderboard

Who's calling PostHog's MCP server the most? We're keeping score every day for our ~~internal purposes~~ and your viewing pleasure.

Last week* Oct 19–25

Updated Oct 30

Anthropic▲ 1.0 pts vs. last week

65.8%

OpenAI▲ 0.3 pts vs. last week

31.2%

xAI▼ 0.0 pts vs. last week

1.7%

Share of last week's tool calls, out of the 74% where we know the model.
* Agents name their own model, except Codex, which sends it in its request metadata. We can't check it, and models sometimes get their own version wrong.

Growth since Jun 22

Each week as a multiple of the baseline week, June 22, 2026.

May the best model win

Which models agents run when they call our tools. Think of it as a popularity contest.

Daily share of tool calls by model

Top 10 models with the most calls get their own band, and each lab's other models share one. Calls without a known model are left out.

Top models last week

claude-opus-5-550.1%▲ 1.9 pts
gpt-612.5%▲ 1.3 pts
gpt-6.1-sol11.5%▲ 0.1 pts
claude-sonnet-5-56.3%▲ 0.2 pts
claude-fable-5-13.2%▼ 0.3 pts
gpt-6-astra2.9%▼ 1.0 pts
claude-sonnet-51.7%▼ 0.4 pts
claude-opus-51.6%▼ 0.4 pts
grok-4.71.4%no change
gpt-6.11.0%▲ 0.4 pts
gpt-51.0%▼ 0.1 pts
claude-opus-40.8%no change
gpt-6-sol0.7%no change
gpt-5.6-sol0.7%▼ 0.2 pts
claude-opus-4-80.6%▲ 0.1 pts

Share of last week's calls with a known model. Changes are against the week before.

AI players battle it out

Daily share of tool calls by AI lab

The lab behind each call's model. Calls without a model are left out.

Top harnesses last week

Claude Code30.1%▼ 0.7 pts
OpenAI (app not named)18.1%▲ 0.5 pts
Cursor10.5%▼ 0.3 pts
Cowork6.9%▲ 0.2 pts
OpenAI Codex4.5%▼ 0.8 pts
Claude Desktop4.0%▲ 0.3 pts
Claude artifacts3.8%▲ 0.7 pts
Claude Agent SDK3.0%▲ 0.1 pts
Claude.ai2.6%▲ 0.1 pts
Claude Code (VS Code)1.5%▼ 0.1 pts
Executor0.6%▼ 0.2 pts
Devin0.4%no change
opencode0.3%no change
MCPorter0.3%▲ 0.1 pts
Amp0.2%no change

The app the agent runs in, colored by who makes it. Not listed: custom code (3.7% of calls), meaning scripts and SDKs that only tell us their HTTP library, like Python's httpx, and apps with fewer than 25 users each (8.9%). Our own CLI isn't counted at all.

The rise and fall of MCP spec versions

MCP spec version, daily share of tool calls

The revision of the MCP spec the client and our server agreed on when they connected. A client moves to a newer one when it updates, so old versions fade out slowly.

How agents sign in

OAuth 89.5%
Personal API key 10.5%

OAuth means the user signed in through the browser when they added the server.
A personal API key means they made a key in PostHog and pasted it into their config.

How we know the model

Agent said so 70.0%
Not reported 25.7%
Client metadata 4.4%

Our server adds an llm_model argument to every tool, and "Agent said so" means the agent filled it in. "Client metadata" means the app sent the model with the request. "Not reported" means neither, so we don't know the model.

What agents are up to

Tool categories

Share of last week's tool calls, by the PostHog product the tool belongs to.

Agents tell us 'why' 90% of the time

How intent works

1. PostHog's MCP analytics adds a context argument to every tool's schema: "Why are you calling this tool? Briefly describe the user's goal."
2. The agent fills it in on each call. The SDK strips it before your handler runs, so your tools never see it.
3. PostHog stores it as $mcp_intent and groups similar intents into themes, so you see the jobs people bring to your server and which ones fail.

What they look like

$mcp_intent: "Comparing signup conversion before and after Tuesday's pricing change"

If an agent skips the argument, the server can derive an intent from the tool and its arguments instead.

Reliability

Error rate

Share of each day's tool calls that came back with an error.

Why calls failed last week

Bad arguments 81.1%
Tool failed 8.2%
API said no (4xx) 4.9%
Rate limited 2.8%
API error (5xx) 1.1%
No permission 0.9%
Memory limit 0.4%
Missing context 0.4%
Timed out 0.3%

Bad arguments: Our server rejected the call before running it: a missing parameter, a wrong type, or a value the tool doesn't take.
Tool failed: The tool ran and something broke. That's either our bug or a query that couldn't run.
API said no (4xx): The PostHog API turned the request down, for example because the thing it asked for doesn't exist.
API error (5xx): The PostHog API had an error of its own.

How long a tool call takes

From when our server gets the call to when it sends the result back, which is mostly PostHog running a query. It doesn't include the model's thinking time or the network.

Bad arguments by model, last week

claude-sonnet-55.7%all errors 6.8%
claude-sonnet-5-53.7%all errors 4.3%
claude-opus-5-53.5%all errors 4.2%
claude-fable-5-13.0%all errors 3.9%
claude-opus-52.7%all errors 3.2%
grok-4.71.5%all errors 2.4%
gpt-6-astra0.9%all errors 1.4%
gpt-60.8%all errors 1.3%
gpt-6.1-sol0.8%all errors 1.3%
gpt-6.10.8%all errors 1.0%

Share of each model's calls that our server rejected because the arguments didn't match the tool's schema, for the ten models with the most calls. This indicates how well a model can follow the MCP protocol: tool discovery, and argument validation.

How this page works

Our MCP server runs MCP analytics on itself. Every tool call lands in PostHog as a $mcp_tool_call event.

Two HogQL queries turn those events into shares, one by week and one by day. Any label with fewer than 25 users in a period folds into "Other".

Each query is a PostHog endpoint that refreshes daily.

When posthog.com builds, Gatsby calls both endpoints and bakes the results into this page.

Data fetched Fri, 30 Oct 2026 00:35:56 GMT.

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