User:
Compare pallets/flask and django/django.

Which repository looks more active?

compare_repos

                ┌─────────────────────┐
                │   MCP Client / AI   │
                │ Claude / MCP Client │
                └──────────┬──────────┘
                           │
                           │ MCP stdio
                           ▼
                ┌─────────────────────┐
                │ GitHub Analytics    │
                │     MCP Server      │
                └──────────┬──────────┘
                           │
                 ┌─────────┴─────────┐
                 │                   │
                 ▼                   ▼
          Input Validation       TTL Cache
                                     │
                           ┌─────────┴─────────┐
                           │                   │
                      CACHE HIT          CACHE MISS
                           │                   │
                           │                   ▼
                           │          Async HTTP Client
                           │                   │
                           │          Retry + Backoff
                           │                   │
                           │                   ▼
                           │            GitHub REST API
                           │                   │
                           └───────────◄───────┘
                                       │
                                       ▼
                               Structured MCP Result

httpx.AsyncClient

connect
read
write
pool

First request

MCP Client
    │
    ▼
MCP Server
    │
    ▼
GitHub API
    │
    ▼
Cache

MCP Client
    │
    ▼
MCP Server
    │
    ▼
CACHE HIT

X-RateLimit-Limit
X-RateLimit-Used
X-RateLimit-Remaining
X-RateLimit-Reset
Retry-After

Attempt 1
   │
   └── failure
        │
        ▼
      wait 1s

Attempt 2
   │
   └── failure
        │
        ▼
      wait 2s

Attempt 3
   │
   └── final result

2 ** (attempt - 1)

2026-08-27T14:14:03 | INFO | Starting GitHub Analytics MCP server
2026-08-27T14:14:04 | INFO | GET /repos/facebook/react → 200
2026-08-27T14:14:04 | INFO | CACHE HIT /repos/facebook/react

letters
numbers
.
-
_

face../../book

repo_a = await get_repo_a()
repo_b = await get_repo_b()

repo_a, repo_b = await asyncio.gather(
    get_repo_a(),
    get_repo_b(),
)

Sequential

Repo A ───────────────► Done
                        Repo B ───────────────► Done


Parallel

Repo A ───────────────► Done
Repo B ───────────────────► Done

get_repo_overview(
    owner="facebook",
    repo="react"
)

list_recent_commits(
    owner="vuejs",
    repo="core",
    limit=5
)

get_contributors(
    owner="django",
    repo="django",
    limit=10
)

list_open_issues(
    owner="pallets",
    repo="flask",
    limit=10
)

compare_repos(
    owner1="pallets",
    repo1="flask",
    owner2="django",
    repo2="django"
)

stars
forks
open issues
language
last push

{
  "limit": 60,
  "used": 4,
  "remaining": 56,
  "resets_in_seconds": 3599,
  "server_outbound_http_requests": 4,
  "server_cache_hits": 1
}

mcp-github-analytics/
│
├── server.py
│   └── Main MCP server and GitHub tools
│
├── demo_mcp.py
│   └── Real end-to-end MCP client demo
│
├── requirements.txt
│   └── Python dependencies
│
├── .env.example
│   └── Environment variable template
│
└── .gitignore

git clone https://github.com/sweta2503/mcp-github-analytics.git

cd mcp-github-analytics

python -m venv .venv

source .venv/bin/activate

.venv\Scripts\activate

pip install -r requirements.txt

mcp[cli]==2.1.1
httpx==0.28.1
python-dotenv==1.2.3

cp .env.example .env

GITHUB_TOKEN=your_github_token_here

python demo_mcp.py

1. Starts server.py as an MCP subprocess
2. Connects using MCP stdio
3. Negotiates the MCP protocol
4. Discovers the MCP tools
5. Calls the tools through MCP
6. Receives structured MCP responses

MCP CONNECTED — discover the real server tools

Negotiated protocol: ...
Tools discovered (7):
get_repo_overview
list_recent_commits
get_contributors
list_open_issues
get_commit_activity
compare_repos
get_rate_limit_status

get_repo_overview(facebook/react)

CACHE HIT

compare_repos(
    pallets/flask,
    django/django
)

asyncio.gather(...)

python demo_mcp.py > demo_output.txt 2> server.log

demo_output.txt

server.log

GET /repos/facebook/react → 200
CACHE HIT /repos/facebook/react
GET /repos/pallets/flask → 200
GET /repos/django/django → 200

python server.py

{
  "mcpServers": {
    "github-analytics": {
      "command": "/ABSOLUTE/PATH/TO/mcp-github-analytics/.venv/bin/python",
      "args": [
        "/ABSOLUTE/PATH/TO/mcp-github-analytics/server.py"
      ],
      "env": {
        "GITHUB_TOKEN": "YOUR_GITHUB_TOKEN"
      }
    }
  }
}

/ABSOLUTE/PATH/TO/mcp-github-analytics

Compare pallets/flask and django/django.

Which repository appears more active?

Use the GitHub MCP tools and explain which data you used.

User
 │
 ▼
Claude / MCP Client
 │
 │ MCP tool call
 ▼
GitHub Analytics MCP Server
 │
 ├── Validate input
 │
 ├── Check TTL cache
 │
 ├── Cache hit ──────────────► Return result
 │
 └── Cache miss
          │
          ▼
     Async HTTP
          │
     Retry / Backoff
          │
          ▼
     GitHub REST API
          │
          ▼
       Response
          │
          ▼
       TTL Cache
          │
          ▼
 Structured MCP Response
          │
          ▼
     AI / MCP Client

Redis
PostgreSQL
distributed rate limiting
centralized observability
authentication
tracing