Commit Historian Agent
Pricing
Pay per event
Commit Historian Agent
Simple tool to help analyze Github repository commits. It checkouts the repository and get all relevant commit messages. It uses OpenAI to answer questions asked by the user. This is done through PydanticAI framework.
0.0 (0)
Pricing
Pay per event
0
Monthly users
1
Runs succeeded
>99%
Last modified
19 days ago
You can access the Commit Historian Agent programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1# Start Server-Sent Events (SSE) session and keep it running
2curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=josef.prochazka/commit-historian-agent"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1faUsing Commit Historian Agent via Model Context Protocol (MCP) server
MCP server lets you use Commit Historian Agent within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the Commit Historian Agent Actor with the provided input.
1curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{
2 "jsonrpc": "2.0",
3 "id": 1,
4 "method": "tools/call",
5 "params": {
6 "arguments": {
7 "prompt": "Show several most complicated changes done last month.",
8 "repository": "apify/crawlee-python"
9},
10 "name": "josef.prochazka/commit-historian-agent"
11 }
12}'The response should be: Accepted. You should received response via SSE (JSON) as:
1event: message
2data: {
3 "result": {
4 "content": [
5 {
6 "type": "text",
7 "text": "ACTOR_RESPONSE"
8 }
9 ]
10 }
11}Configure local MCP Server via standard input/output for Commit Historian Agent
You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:
1{
2 "mcpServers": {
3 "actors-mcp-server": {
4 "command": "npx",
5 "args": [
6 "-y",
7 "@apify/actors-mcp-server",
8 "--actors",
9 "josef.prochazka/commit-historian-agent"
10 ],
11 "env": {
12 "APIFY_TOKEN": "<YOUR_API_TOKEN>"
13 }
14 }
15 }
16}You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.
To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.
Pricing
Pricing model
Pay per eventThis Actor is paid per result. You are not charged for the Apify platform usage, but only a fixed price for each dataset of 1,000 items in the Actor outputs.
Own OpenAPI key
$0.020
When you use your own OpenAPI key
Apify OpenAPI key
$0.100
When you use your Apify OpenAPI key
