wincher-mcp 0.2.1

Read-only Wincher SEO MCP server for Cursor, Claude Code, and other stdio MCP hosts

Wincher MCP

Read-only Wincher SEO data for AI coding agents.
Connect Cursor, Claude Code, or any MCP client to your tracked websites: keyword rankings, competitors, SERPs, and groups, without leaving the editor.

• Read-only by design — GET-style Wincher API usage only; no writes to your account
• Stdio MCP — local process spawned by the client; no HTTP listener
• Nine focused tools — websites, keywords, rankings, competitors, SERPs, groups, bulk history, annotations
• Hardened defaults — input limits, response caps, safe errors, optional staging host validation
• Optional TOON output — compact Token-Oriented Object Notation responses to cut LLM token use on large keyword and ranking lists

Canonical open-source Wincher MCP server: PyPI package wincher-mcp, agent docs, CI, vendored OpenAPI, optional TOON output, and security hardening. Lineage from the early chris-tutt/wincher-mcp-server prototype; this repo is the maintained home for new work.

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Table of contents

• Why use this
• Features
• Quick start
• Requirements
• Installation
• Authentication
• Connect your MCP client
• Tools reference
• Example prompts for agents
• Security
• API reference
• Troubleshooting
• Development
• Lineage and license

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Why use this

Wincher holds the keyword and competitor data SEO workflows depend on. This server exposes that data through the Model Context Protocol so agents can answer questions in chat instead of exporting CSVs or clicking through dashboards.

Use it when you want:

• Website and keyword lists inside an agent session
• Competitor and SERP context for a target query
• A small, auditable tool surface (nine read-only tools)

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Features

Capability	MCP tool
List tracked websites	get_websites
Keywords and current rankings	get_keywords
Historical ranking series	get_keyword_rankings
Competitor summary metrics	get_competitor_ranking_summaries
Competitor positions per keyword	get_competitor_keyword_positions
SERP snapshot and features	get_serps
Keyword group aggregates	get_keyword_groups
Bulk ranking history	get_bulk_ranking_history
SEO annotations / notes	get_annotations

Input validation — Positive integer IDs, bounded bulk lists, validated date strings where applicable.

Clear errors — HTTP failures return endpoint and status without leaking full URLs, tokens, or raw API bodies.

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Quick start

Agentic install prompt

Paste into Cursor, Claude Code, or Copilot and ask the agent to run setup on your machine.

Assumptions (confirm before changing anything):

Assumption	Why it matters
Python 3.10+	Required to run wincher_mcp_server.py
Wincher account	Personal Access Token from Wincher settings
Stdio MCP	Config uses command + args; no HTTP transport
Absolute paths	MCP config must point at real .venv/bin/python and wincher_mcp_server.py
Secrets off-repo	WINCHER_API_KEY in MCP env or ~/.zsh_secrets, never committed

Set up the wincher-mcp MCP server from https://github.com/vmandic/wincher-mcp on this machine end-to-end.

Before you change anything, confirm with me:
1) Which MCP client I use (Cursor, Claude Code, or VS Code Copilot).
2) Where to clone the repo (default: ~/source/vmandic/wincher-mcp).

Then:

A) Prerequisites — Python 3.10+, no secrets in git.
B) Clone, venv, test — git clone, python3 -m venv .venv, pip install -r requirements.txt -r requirements-dev.txt, pytest -q, py_compile wincher_mcp_server.py.
C) Wincher token — I create a Personal Access Token in Wincher; add WINCHER_API_KEY to MCP env (or ~/.zsh_secrets if using a wrapper script).
D) MCP config — stdio: command = ABSOLUTE_PATH/.venv/bin/python, args = [ABSOLUTE_PATH/wincher_mcp_server.py], env = { WINCHER_API_KEY }. See docs/MCP_CONFIG.example.json. Do not commit real keys or staging hosts.
E) Verify — restart MCP client, call get_websites, report results or auth errors.

Summarize: clone path, config file edited, and exact JSON used.

Manual setup

1. Clone and install

git clone https://github.com/vmandic/wincher-mcp.git
cd wincher-mcp
python3 -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -r requirements.txt

2. API key — Wincher → Settings → Personal Access Tokens. Copy the token once; store it only in env or a local secrets file.

3. MCP client — example for Cursor (~/.cursor/mcp.json):

{
  "mcpServers": {
    "wincher-mcp": {
      "command": "/absolute/path/to/wincher-mcp/.venv/bin/python",
      "args": ["/absolute/path/to/wincher-mcp/wincher_mcp_server.py"],
      "env": {
        "WINCHER_API_KEY": "YOUR_KEY_HERE"
      }
    }
  }
}

See docs/MCP_CONFIG.example.json for production, optional staging, and TOON entries.

4. Restart the client, then ask: “List my Wincher websites” (get_websites).

Full walkthrough: docs/SETUP.md. More prompts: docs/EXAMPLES.md.

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Requirements

Requirement	Notes
Python	3.10 or newer (CI tests 3.10–3.12)
Wincher account	With API access and tracked sites/keywords
API token	Personal Access Token; env var WINCHER_API_KEY
MCP client	Cursor, Claude Code, or any stdio MCP host

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Installation

From PyPI (recommended)

pipx install wincher-mcp
# or: pip install wincher-mcp

MCP config then uses the console script (no clone path):

{
  "mcpServers": {
    "wincher": {
      "command": "wincher-mcp",
      "args": [],
      "env": { "WINCHER_API_KEY": "YOUR_KEY_HERE" }
    }
  }
}

Find the binary path if needed: pipx which wincher-mcp.

Package: pypi.org/project/wincher-mcp. Publishing: docs/PYPI.md.

From a clone (development)

git clone https://github.com/vmandic/wincher-mcp.git
cd wincher-mcp
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
pytest -q

Legacy launcher wincher_mcp_server.py at repo root still works for existing MCP JSON paths.

Virtual environment name

Use .venv (as in CI) or pipx for MCP hosts. Update MCP config command accordingly.

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Authentication

The server never stores tokens on disk. It reads WINCHER_API_KEY from the process environment (set in MCP env or exported in the shell).

What	Purpose
Personal Access Token	Bearer auth to https://api.wincher.com (production)
Optional staging	MCP arg "--use-staging" plus env WINCHER_STAGING_API_HOST on your machine only

Production API host is hardcoded in the server. The staging host must never be committed to this repository.

Obtain staging URLs from your Wincher team; wire them only in private MCP config. See docs/MCP_CONFIG.example.json (wincher-staging has no host in the example).

Optional TOON responses (lower token use)

TOON is a compact encoding for structured data sent to LLMs. Tabular Wincher payloads (keywords, competitors, bulk history) often use 30–60% fewer tokens than the default human-readable text layout.

Mode	How
Server default TOON	Add "--use-toon" to the MCP server args array (see wincher-toon in docs/MCP_CONFIG.example.json)
Per call	Pass "output_format": "toon" on any tool (or "text" to force readable text when --use-toon is on)

Responses include a short preamble and TOON body. Decode in Python with python-toon:

from toon import decode

Default remains human-readable text when --use-toon is not set.

Wrapper pattern (optional): a shell script can source ~/.zsh_secrets then exec .venv/bin/python wincher_mcp_server.py so Cursor opened from the Dock still gets the key. Do not commit that script with secrets inside.

Copy .env.example to .env for local shell use only; .env is gitignored.

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Connect your MCP client

Client	Config location	Config key
Cursor	~/.cursor/mcp.json or project .cursor/mcp.json	mcpServers
Claude Code	~/.claude.json or project .mcp.json	mcpServers
VS Code Copilot	.vscode/mcp.json	servers (stdio)

The Claude desktop app (if you use it) uses claude_desktop_config.json on macOS/Windows with the same mcpServers shape; see docs/SETUP.md.

All examples use stdio: the client spawns Python and talks JSON-RPC over stdin/stdout. Logs and errors go to stderr.

Project-level MCP: some repos commit .cursor/mcp.json with a command pointing at a local wrapper (no secrets in JSON). Global user config can hold the same server for all workspaces.

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Tools reference

All tools are read-only. Parameters use Wincher website/keyword IDs from get_websites / get_keywords.

Tool	Main inputs
get_websites	—
get_keywords	website_id
get_keyword_rankings	website_id, keyword_id, date range
get_competitor_ranking_summaries	website_id
get_competitor_keyword_positions	website_id, competitor filters
get_serps	website_id, keyword_id
get_keyword_groups	website_id
get_bulk_ranking_history	website_id, keyword id list (capped)
get_annotations	website_id

Field-level detail: vendored docs/api/wincher-openapi.json and Wincher API docs.

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Example prompts for agents

• “List all websites in my Wincher account.”
• “For website ID 12345, show keywords in the top 10.”
• “Compare our rankings vs competitor X for this site.”
• “Show the SERP for keyword ID 67890.”
• “Which keyword group has the best average position?”

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Security

This server calls your Wincher account using your API token. Treat it like any local tool with outbound HTTPS.

What we enforce in code

Control	Detail
Read-only tools	No create/update/delete Wincher resources
Stdio only	No network listener in the server
Production host fixed	https://api.wincher.com in source
Staging URL validation	HTTPS only; blocks localhost/private/metadata hosts
No redirect following	follow_redirects=False on HTTP client
Bounded inputs/outputs	ID validation, bulk caps, row limits in formatted responses
Error redaction	Tool errors avoid tokens and full response bodies

What you should do

1. Never commit .env, real MCP JSON with keys, or WINCHER_STAGING_API_HOST values.
2. Prefer project gitignore for .cursor/mcp.json if it might hold local paths tied to secrets workflow.
3. Review security_best_practices_report.md for the full audit and residual risks (including SSRF if staging env is mis-set).

Threat model (short)

Mode	Who can call tools?
stdio	The MCP client that started the Python process (your IDE / agent host)

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API reference

OpenAPI is vendored from wincher.com/docs/api:

File	Role
docs/api/wincher-openapi.json	Spec snapshot
docs/api/META.json	fetched_at, source_chunk_sha256
docs/api/README.md	Refresh instructions

Refresh locally:

python3 scripts/fetch_wincher_openapi.py

CI runs a weekly drift check (scripts/fetch_wincher_openapi.py --check) against META.json.

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Troubleshooting

Symptom	What to try
MCP server not listed	Restart client; check absolute paths to .venv/bin/python and wincher_mcp_server.py.
WINCHER_API_KEY not set	Add token to MCP env or wrapper that sources your secrets file.
HTTP 401	Regenerate token in Wincher; update env; restart client.
Empty or partial data	Confirm sites/keywords exist in Wincher UI; check website/keyword IDs.
Staging errors	Ensure --use-staging in args and WINCHER_STAGING_API_HOST set in env (host not in repo).

Test API key manually:

curl -sS -H "Authorization: Bearer YOUR_KEY" https://api.wincher.com/v1/websites

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Development

Every push and pull request to main runs CI:

Job	What it does
test	Python 3.10 / 3.11 / 3.12 — pip install, py_compile, pytest, pip-audit
api-spec-check	Weekly (and on schedule) — verify Wincher docs chunk hash vs docs/api/META.json

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt -r requirements-dev.txt
pytest -q
pip-audit -r requirements.txt -r requirements-dev.txt
python3 scripts/fetch_wincher_openapi.py          # refresh spec
python3 scripts/fetch_wincher_openapi.py --check  # drift check

Layout:

wincher_mcp_server.py   # MCP entry (stdio)
scripts/                # OpenAPI fetch
docs/api/               # Vendored spec + META
test/                   # pytest (security, fetch script)
.cursor/                # Agent rules and skills
AGENTS.md               # Pointer for coding agents

Agents: start with AGENTS.md and .cursor/rules/.

Dependabot: .github/dependabot.yml (pip + GitHub Actions).

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Lineage and license

Item	Link
Repository	github.com/vmandic/wincher-mcp
PyPI	pypi.org/project/wincher-mcp
Early prototype	github.com/chris-tutt/wincher-mcp-server
Wincher API	wincher.com/docs/api
MCP SDK	modelcontextprotocol/python-sdk

MIT — maintained by Vedran Mandić and contributors.

Contributions welcome via issues and pull requests. Run pytest and pip-audit before opening a PR.