chore: add readme for ts package (#111)

Author: joshsny

.gitignore

@@ -17,4 +17,6 @@ __pycache__/
 
 .env
 
-dist/
+dist/
+
+.venv/

typescript/README.md

@@ -0,0 +1,70 @@
+# @posthog/agent-toolkit
+
+Tools to give agents access to your PostHog data, manage feature flags, create insights, and more.
+
+## Installation
+
+```bash
+npm install @posthog/agent-toolkit
+```
+
+## Quick Start
+
+The toolkit provides integrations for popular AI frameworks:
+
+### Using with Vercel AI SDK
+
+```typescript
+import { openai } from "@ai-sdk/openai";
+import { PostHogAgentToolkit } from "@posthog/agent-toolkit/integrations/ai-sdk";
+import { generateText } from "ai";
+
+const toolkit = new PostHogAgentToolkit({
+    posthogPersonalApiKey: process.env.POSTHOG_PERSONAL_API_KEY!,
+    posthogApiBaseUrl: "https://us.posthog.com" // or https://eu.posthog.com if you are hosting in the EU
+});
+
+const result = await generateText({
+    model: openai("gpt-4"),
+    tools: toolkit.getTools(),
+    prompt: "Analyze our product usage by getting the top 5 most interesting insights and summarising the data from them."
+});
+```
+
+**[→ See full Vercel AI SDK example](https://github.com/posthog/mcp/tree/main/examples/ai-sdk)**
+
+### Using with LangChain.js
+
+```typescript
+import { ChatOpenAI } from "@langchain/openai";
+import { PostHogAgentToolkit } from "@posthog/agent-toolkit/integrations/langchain";
+import { AgentExecutor, createToolCallingAgent } from "langchain/agents";
+import { ChatPromptTemplate, MessagesPlaceholder } from "@langchain/core/prompts";
+
+const toolkit = new PostHogAgentToolkit({
+    posthogPersonalApiKey: process.env.POSTHOG_PERSONAL_API_KEY!,
+    posthogApiBaseUrl: "https://us.posthog.com" // or https://eu.posthog.com if you are hosting in the EU
+});
+
+const tools = toolkit.getTools();
+const llm = new ChatOpenAI({ model: "gpt-4" });
+
+const prompt = ChatPromptTemplate.fromMessages([
+    ["system", "You are a data analyst with access to PostHog analytics"],
+    ["human", "{input}"],
+    new MessagesPlaceholder("agent_scratchpad"),
+]);
+
+const agent = createToolCallingAgent({ llm, tools, prompt });
+const executor = new AgentExecutor({ agent, tools });
+
+const result = await executor.invoke({
+    input: "Analyze our product usage by getting the top 5 most interesting insights and summarising the data from them."
+});
+```
+
+**[→ See full LangChain.js example](https://github.com/posthog/mcp/tree/main/examples/langchain-js)**
+
+## Available Tools
+
+For a list of all available tools, please see the [docs](https://posthog.com/docs/model-context-protocol).