A companion skill for the Peec AI MCP server. Drop it into any MCP-capable AI agent (Claude, Cursor, Codex, n8n, etc.) to get correct, actionable guidance on how to use the Peec MCP — including the gotchas the official docs omit or get wrong.
Released under CC BY 4.0. Reuse, adapt, redistribute — keep the attribution.
Value scales with task complexity. This is a comprehensive reference (~29k words / ~40k tokens when loaded) designed to replace trial-and-error on multi-step Peec work — full visibility reports, per-engine comparisons, competitive gap analysis, source-authority audits, project tune-ups. For trivial single-tool lookups like
list_projectsorlist_brands, Peec's own tool descriptions are usually enough; the frontmatter deliberately avoids triggering on those. The payoff lands on tasks where data-interpretation gotchas (sentiment scale, position semantics, retrieval-vs-citation,get_actionstwo-step workflow,list_prompts.volumetype coercion,get_url_contentrefresh cadence) or schema asymmetries (§7.39, §7.31) would otherwise produce confidently wrong output. Internal A/B testing across complexity tiers (simple lookups → deep multi-step audits) showed skill-assisted runs on the complex tier produced materially more correct output at a modest token cost, while the simple tier saw effectively no benefit — which is why the description is scoped to analysis and multi-step work, not every Peec mention.
- Data model clarity. Brands, prompts, topics, and tags are orthogonal in Peec — no
brand_idforeign key on prompts, no write path to "assign" prompts to brands. The skill makes this explicit so agents don't attempt impossible workflows. - All 27 MCP tools (15 read-only, 8 write, 4 destructive) with correct usage.
- 7 slash-command prompts (
/peec_weekly_pulseetc.) and when to use each. - 42 data-literacy gotchas. Scales are mixed within a single row,
positionmeans rank-among-tracked-brands not overall,list_modelsreturns 16 engines while themodel_idfilter enum lists 19, the sentiment formula isn't what the docs imply,get_actionsis reliably callable from pass-through clients (schema-strict clients strip params — fallback recipe included),retrieval_rateandcitation_ratecan exceed 1.0, domain and URL reports return different types for the same-named columns, engine-returned empty response bodies silently inflate non-mention counts,get_brand_reportdimension labels can return null within the first 24h after a prompt-write wave,list_search_queries(fanout) returns zero rows for AI Overview, AI Mode, and Copilot but is confirmed to return data for ChatGPT and Grok,list_prompts.volumereturns string ordinals (not the 1–5 integers the schema claims), and more. - Hidden features — the
gapfilter on domain/URL reports,mentioned_brand_countfilter,regexoncreate_brand, wave-based execution for bulk changes, scraped content viaget_url_content(with the 5-day refresh cadence and dual classification fields documented). - 11 composite recipes covering the analyses people actually want to run — full visibility reports, per-engine head-to-head comparisons, competitive gap analysis, source authority audit, safe test-entity lifecycle, and more.
| File | Purpose |
|---|---|
SKILL.md |
The core: data model, quick start, pre-flight checklist, setup, and a section map saying when to load each reference file. |
references/ |
The detailed surface, loaded on demand: tools & response format (§3–§5), power features (§6), the data-literacy gotcha catalogue (§7), and composite recipes (§8). Section numbering is global across the file set. |
CONTRIBUTING.md |
How to propose changes. |
LICENSE |
CC BY 4.0. |
For connecting the Peec MCP server to your client, follow Peec's official setup docs at docs.peec.ai/mcp/introduction. This skill deliberately doesn't duplicate that content — Peec maintains the up-to-date client list and connection flows.
Skills load from your Cowork mount's .claude/skills/ directory. Clone into there, restart the app, and the skill's description will trigger on Peec-related queries.
# macOS path — adjust for your system
cd ~/Library/Application\ Support/Claude/skills
git clone https://github.com/rebelytics/peec-ai-mcp peec-ai-mcpmkdir -p .claude/skills
git clone https://github.com/rebelytics/peec-ai-mcp .claude/skills/peec-ai-mcpClaude Code will pick the skill up automatically from the project's skills directory.
These clients don't have a unified skills model yet. For now, copy the skill directory (SKILL.md plus references/) into your project and reference it explicitly in your AI context (e.g. via Cursor's @Files or VS Code's context pinning).
Place the skill directory under ~/.codex/skills/peec-ai-mcp/ (keeping SKILL.md and references/ together) if you're running a Codex version that supports skill files, or reference the content explicitly in your prompt preamble.
n8n doesn't have a skill concept. Include the relevant sections of the skill (especially references/gotchas.md, the §7 data-literacy catalogue) in the system prompt of any workflow that calls Peec MCP.
Installing the skill doesn't connect your agent to Peec — you still need to add the Peec MCP server to your client. Follow Peec's official per-client setup instructions at docs.peec.ai/mcp/introduction.
The Peec MCP server exposes a rich 27-tool surface, but the official documentation (a) doesn't explain several critical data-interpretation subtleties that lead agents to produce confidently wrong analysis, and (b) doesn't cover all client apps. This skill fills those gaps.
The goal is that any agent — Claude, Cursor, Codex, n8n, whatever comes next — loads this skill and gets behaviour grounded in how Peec actually responds, not how the docs say it should.
Found a discrepancy? Hit a bug? Discovered a new tool, parameter, or client app that works? Open an issue or a PR.
See CONTRIBUTING.md for what's in scope and how to submit changes.
- Author: Eoghan Henn / LinkedIn
- Not affiliated with Peec AI. They make the product; this skill is an independent guide.
CC BY 4.0 — the licence text is in LICENSE: the full legal code, unmodified, as Creative Commons publishes it; the human-readable summary says what it allows. Use it, fork it, adapt it, monetise it. Keep the attribution.
Copyright (c) 2026 Eoghan Henn / rebelytics.com