Model Context Protocol

The competitive intelligence layer for your AI stack.

MCP is an open standard that lets AI assistants and agents connect directly to external tools and data. The Flares MCP exposes your competitive data — battlecards, reports, signals — to any AI agent, and lets you push intelligence from any source back into Flares.

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14-day free trial · 30-second setup

Powering the world’s best companies

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Build custom competitive intelligence workflows.

Stop doing manually what your AI agents can do for you automatically — 24/7.

Before every sales call

Your AI assistant pulls the latest battlecard for the competitor on the deal — objection handlers, positioning, pricing — seconds before the call starts.

Automated weekly briefs

An agent reads recent signals from Flares and writes a stakeholder summary, then posts it to Slack or your internal wiki. No manual work.

CRM enrichment, from any CRM

Connect Pipedrive, Attio, or any other CRM via their own MCP. An agent reads closed deals, extracts competitive context, and writes it back to Flares.

Custom signal pipelines

Monitor patent, job boards, news feeds or any relevant sources with an agent, then push relevant competitive signals directly into your Flares competitor reports.

Up and running in minutes.

01

Install the Flares MCP

Add Flares to your AI agent or assistant in one command. Works with any MCP-compatible client.

$npx -y @flares/mcp
02

Connect your workspace

Authenticate with your Flares API key. Your competitors, reports, and battlecards are instantly available.

$FLARES_API_KEY=flares_sk_••••••••••••
03

Build your workflows

Call Flares tools from any agent. Read competitive data, push signals from external sources, automate briefings.

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Competitive intelligence MCP tools your AI agents need.

Read your competitive data and write back from any source to supercharge your intelligence.

~/flares/mcp

// read

get_battlecard()

Fetch the full battlecard for a competitor, or a specific section.

get_competitor_report()

Get a structured competitive report — pricing, features, recent changes.

list_recent_signals()

List the latest signals captured for one or all competitors.

compare_competitors()

Side-by-side comparison of features or pricing across multiple competitors.

search_competitors()

Find competitors matching a description or market segment.

get_digests()

Retrieve past competitive digests, optionally filtered by competitor or date range.

get_competitor_schema()

Get the full business schema of a competitor — all fields, sections, and structured data that make up their profile.

get_own_business_schema()

Get your own company's business schema — positioning, product, pricing, and more — to give agents the full competitive context.

// write

add_competitor()

Add a new competitor to your Flares workspace by URL.

analyze_url()

Submit any URL and get a structured competitive signal back.

submit_signal()

Push a competitive signal from any source into a competitor profile.

submit_win_loss()

Record a win or loss outcome linked to a competitor.

enrich_competitor()

Update a specific data point on a competitor from field intelligence.

Works with any AI assistant or coding agent, out of the box.

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Ready? Your competitors won't wait for you.

Get your first competitive digest next Monday.

14-day free trial · 30-second setup