Documentation
An AI agent as your team's strategist via MCP
Connect Claude, ChatGPT, Cursor, or Claude Code — and the team gains a strategist with direct access to the full monitoring picture. A connection guide plus examples: root-cause gap analysis, article briefs, reports — all in chat
Open in dashboardAn AI agent as your team's strategist
With MCP you add a strategist to the team — one who works with monitoring data at a depth the UI can't reach. It reads full AI responses, breaks down every cited source, compares with competitors, iterates on hypotheses, and assembles strategy and briefs. Ask "why does AI answer this way", "what should the article look like to land in this prompt", "give me a quarterly content roadmap" — and get a full analytical breakdown, not a rehash of dashboard numbers. The strategist can be Claude, ChatGPT, Cursor, or any other MCP-compatible AI. Technically, MCP (Model Context Protocol) is the standard that gives the agent this access.
- Strategist clients: Claude Desktop, ChatGPT (via Custom Connectors), Cursor, Claude Code, Codex, or any other MCP-compatible client
- Connect via OAuth (pick the brand on the GEO Scout consent screen) or via a Personal Access Token (PAT) for scripts and self-hosted clients
- Scoped access — the strategist reads analytics data and can use approved write tools, such as prompt, cluster, campaign, and monitoring rotation changes
- The strategist has access to everything in the dashboard plus the full text of AI responses: metrics, sources, competitors, prompts, citations, actions, content plans, and monitoring settings
An AI strategist isn't a lightweight alternative to the dashboard. It's a layer of deep work on top of the data: the work a senior marketer or external consultant typically spends days on gets done in one evening of conversation. The dashboard shows cuts, the command center sets priorities, the AI strategist does the analytics and strategy.
Claude Desktop
Claude Desktop speaks the stdio MCP protocol, so it connects to the HTTP server through the mcp-remote bridge (an npm package). npx installs it automatically — you only need Node.js 18+ on your machine.
- Open `claude_desktop_config.json` (macOS: `~/Library/Application Support/Claude/`, Windows: `%APPDATA%\Claude\`). If the file doesn't exist, create it
- Add an `mcpServers` block with the command `npx -y mcp-remote https://geoscout.pro/api/mcp` (the exact JSON snippet is on the /mcp page in the dashboard, in the Claude Desktop section)
- Save the file and fully restart Claude Desktop. On first launch npx downloads mcp-remote and opens a browser for OAuth authorization
- On the GEO Scout consent screen, pick the brand the agent should access and confirm. You can connect multiple brands via separate MCP servers in the same config
- An MCP server indicator appears at the bottom of the Claude Desktop chat window — that's the live connection
For PAT access, add `--header "Authorization: Bearer gs_<your-token>"` to args. On Windows, there's a known mcp-remote quirk with space escaping — set the token via an `AUTH_HEADER` env var (value `Bearer gs_...`) and reference it in args as `Authorization:$AUTH_HEADER`. Exact snippets are on the /mcp page.
ChatGPT (Custom Connectors)
ChatGPT supports remote MCP servers via Custom Connectors on paid plans (Plus, Pro, Team, Enterprise). Setup is fully UI-driven — no config files.
- Open chatgpt.com → Settings → Connectors → "Add custom connector"
- Paste the URL `https://geoscout.pro/api/mcp` and click "Add"
- ChatGPT auto-discovers the OAuth metadata and opens the GEO Scout consent screen — pick a brand and approve
- The connector activates immediately. In a new chat, attach it via the paperclip and ask about your brand in natural language
Cursor
Cursor connects MCP servers through the "Connect to a custom MCP" UI form — no JSON files to edit. Works as a global connection or project-only.
- Open Cursor → Settings → MCP servers → "+ Add server"
- Fill in the dialog: Name = `geoscout`, Transport = `Streamable HTTP`, URL = `https://geoscout.pro/api/mcp`
- Save — Cursor opens a browser for OAuth and you pick a brand on the GEO Scout consent screen
- For PAT instead of OAuth: under Headers click "+ Add header", Key = `Authorization`, Value = `Bearer gs_<your-token>`
- After saving, the server appears in the MCP servers list — the tools icon is available in Composer and Chat
To connect the server for one project only, drop a `.cursor/mcp.json` file with the same config in the repo root — Cursor picks it up automatically and the connection won't leak into other projects.
Claude Code CLI
Claude Code uses a one-line `claude mcp add` connect. OAuth runs in the browser, and the config is saved in the project.
- From the project root: `claude mcp add --transport http geoscout https://geoscout.pro/api/mcp`
- Claude Code opens a browser for OAuth automatically. The `--transport http` flag is required for streamable HTTP MCP
- On the GEO Scout consent screen, pick a brand and approve
- The connection is saved in the project's `.claude/` folder. For PAT add `--header "Authorization: Bearer gs_<token>"`
Browser agent (WebMCP)
The same strategist, with zero config. If your browser supports WebMCP (a W3C draft built on the navigator.modelContext API), GEO Scout exposes its read-only tools to the AI agent running right in the tab. No token, no OAuth — the agent acts as your session and sees the current brand's data. It's the shortest path to analysis: open the dashboard and ask «why did we drop out of this prompt» in the same place you read the numbers.
- Zero setup — the current brand's tools are exposed to the browser agent automatically when you open the dashboard
- Read-only: visibility, Share of Voice, citations, competitors, sources, content plans. Writes (prompts, clusters) stay with OAuth/PAT
- Authorized by the browser session — no separate token, access to exactly the brands you see in the UI
- Available today in Chrome 146+ Canary behind the «WebMCP for testing» flag; the standard is early and browser support will grow
WebMCP complements OAuth/PAT rather than replacing them. For writes, scripts, and external clients (Claude Desktop, Cursor) use a token connection; WebMCP is the quick read-only strategist in the same window where you already work.
Your first question — where to start
Once connected, try a light question — the agent figures out which tools to use. Ask in plain language; you don't need to know any API method names.
- "Give me the weekly brand brief" — the agent returns coverage, Share of Voice, Citation Share, top gaps, and quick-win actions
- "Show me the top 10 sources AI cites about my brand" — a map of reference domains with categories (media, marketplaces, forums, competitors)
- "Which prompts are competitors beating us on the most?" — list of gap prompts with deltas and the top competitor per prompt
- "Pull the top 3 negative responses from this week" — AI responses with negative sentiment plus context and provider
Don't guess tool names — describe the task. The agent picks from the available MCP methods and chains them as needed. If a follow-up confuses the agent, rephrase: "Based on monthly monitoring data, …"
Example: gap analysis down to root cause
A real workflow for an e-commerce brand: from spotting a gap to understanding why AI cites competitors. Each step is just a question in chat, all in one conversation.
- Step 1: "Where are competitors beating us the most?" — agent finds the top 5 prompts with the largest gap
- Step 2: "Take prompt #1 and tell me who AI cites and why" — detailed source breakdown and named competitors
- Step 3: agent returns which domains are cited (e.g. retail.ru via a competitor case study), which competitors are mentioned in text, and what content they use
- Step 4: "Why doesn't our brand show up there?" — agent compares your data with the competitor's and points to missing signals (no category page, no top-tier media mention, no JSON-LD markup)
- Step 5: all of this in one chat conversation. No need to open the dashboard, switch filters, or stitch findings by hand
The strength of MCP is exactly this — asking "why" and "what if". The dashboard shows how things stand; MCP lets you dig for causes and find non-obvious connections. One conversation with the agent typically replaces 1–2 hours of manual dashboard work.
Example: drafting an article brief
Once a gap is understood, ask the agent to produce an article brief. It has everything it needs: the gap prompt, competitor-cited sources, key entities from AI responses, your brand facts and certifications.
- Prompt: "Based on this gap, draft an article brief: title, URL, target key entities, schema markup"
- The agent pulls the gap-prompt text, the list of competitor-cited domains, topical entities from 50+ AI responses, and your brand profile
- Output: title and URL for the publication, target key entities (must-mention items), JSON-LD blocks (Article + FAQPage), and reference formats from retail.ru / vc.ru / Habr
- Save the brief to Notion / Linear / Jira via your AI's integrations (Claude — Tool Use; ChatGPT — connectors; Cursor — copy-paste)
- After publishing, ask the agent to track impact 30 days later: "In a month, check whether this URL appears in AI responses and how Citation Share for the topic changed"
Brief quality depends on how you ask. Good templates: "give me 5 key entities", "suggest schema blocks", "find 3 facts about my brand from monitoring that would strengthen citation". The more specific the request, the denser the result.
Example: monthly / weekly report
Replace manual report-stitching with one command to the agent. It collects the numbers, dynamics, and main shifts, and produces text you can send straight to a stakeholder or into a team chat.
- Prompt: "Prepare a monthly brand report — metric dynamics, top providers, major shifts, recommendations for next month"
- The agent calls get_brand_metrics, get_brand_metrics_timeseries, list_competitors, get_competitive_gaps and compares periods (month-over-month or week-over-week)
- Output: a structured text report with numbers, provider breakdown, shift explanations, and priority suggestions
- Follow up with refinements: "give me 3 hypotheses for the SoV drop on Perplexity", "propose 5 actions for next month based on current gaps"
What data the agent can access
Through MCP the agent gets read tools for analytics and scoped write tools for selected operations. You don't need to memorize them — the agent picks the right one for each question.
- Metrics: coverage, Share of Voice, Citation Share, URL mention rate — by period, provider, and prompt cluster, with period-over-period deltas
- Sources: cited domains with categories (media, catalogs, marketplaces, forums), individual URLs, competitor comparison, uncited pages on your site
- Competitors: list of active competitors, head-to-head on any metric, competitive gaps by cluster, mention dynamics
- Prompts and responses: top gap prompts, per-prompt details with full AI responses, sentiment, scores, citations, mentioned competitors
- Actions and content plans: command center tasks, content plans with article structure, published pieces and their measured impact
- Monitoring settings: provider slot rotation, cluster rotation by slot, and the current cycle day
The full list of available tools with descriptions is on the /mcp page in the dashboard. Need a tool or data cut that isn't there yet? Message support — the MCP toolset is actively expanding.