Market analysis — March 2026

3 Tools to Build
& Ship Right Now

Solo-dev-friendly products in the AI tooling space that can reach real traction fast. No teams, no hardware, no enterprise sales cycles — just code, ship, and grow.

Explore the ideas ↓ Skip to verdict
Selection criteria
Why these 3 and not the others?
We filtered every 2026 tech trend through four constraints. Only ideas that pass all four made the cut.
⚡
Time to MVP
≤ 3 weeks solo
🛠
Dependencies
Code only, no hardware
🌱
Distribution
Built-in organic channel
💰
Revenue path
Clear freemium model
❌  What didn't make the cut
  • Spatial Computing — Requires headset SDKs, immature ecosystem, high barrier
  • Green Tech Carbon Calculators — B2B enterprise sales cycle, slow adoption
  • Decentralized Identity Hubs — Needs enterprise partnerships and regulatory alignment
  • On-device Health AI — Regulated industry, app store gatekeeping, compliance overhead
01
LLM Radar
The "Datadog for LLM calls" — a lightweight SDK + dashboard that gives developers instant visibility into every AI API call: cost, latency, token usage, error rates, and prompt versioning. Because right now, teams are burning money blind.
⏱ MVP: 2–3 weeks 🎯 TAM: $4.2B by 2027 📈 Traction: Open-source SDK play
💡 The Problem

Every company using OpenAI, Anthropic, or Google AI is hemorrhaging money with zero visibility into their LLM spend. Engineers have no idea which prompts are expensive, which are slow, or which are failing silently.


Existing solutions like Helicone and LangSmith are either too complex, too locked into specific frameworks, or require significant setup. There's a massive gap for a drop-in, framework-agnostic solution.

🌟 Why Now
  • Enterprise AI spend is projected to hit $200B+ in 2026 — but observability tooling is stuck in 2023
  • Multi-model is the norm now (GPT-4o, Claude, Gemini in the same app) — no one tracks cost across providers
  • The "AI bill shock" meme is real — CTOs are demanding visibility
  • OpenTelemetry for LLMs is still not standardized — first mover defines the spec
🔧 How It Works
  • TypeScript SDK — wraps any LLM client (OpenAI, Anthropic, etc.) as middleware, zero config
  • Auto-capture — intercepts every call, logs tokens, latency, cost, model, prompt hash
  • Dashboard — Next.js app showing real-time spend, per-feature breakdown, anomaly alerts
  • Prompt versioning — automatic diffing so you can correlate prompt changes with cost/quality changes
🚀 Go-to-Market
  • Open-source the SDK on GitHub (MIT license) — devs adopt tools that save them money
  • Post launch on Hacker News, r/programming, Dev.to — "I built Datadog for LLM calls"
  • Free hosted tier (10K events/mo) to drive adoption, then paid for teams
  • Integration docs for LangChain, Vercel AI SDK, LlamaIndex — meet developers where they are
app.ts — 3 lines to integrate
import { LLMRadar } from '@llm-radar/sdk' import OpenAI from 'openai' // Wrap your client — that's it const openai = LLMRadar.wrap(new OpenAI(), { project: 'my-saas', environment: 'production' }) // Use it exactly the same way — costs tracked automatically const response = await openai.chat.completions.create({ model: 'gpt-4o', messages: [{ role: 'user', content: prompt }] }) // Dashboard → $0.03 | 847 tokens | 1.2s | gpt-4o | feature:chat
🛠 Recommended Tech Stack
TypeScript Next.js 14 ClickHouse Postgres tRPC Tailwind CSS Vercel Turborepo
💰 Revenue Model
Free
$0
10K events/mo
7-day retention
1 project
Pro
$29/mo
500K events/mo
90-day retention
Unlimited projects
Team
$99/mo
5M events/mo
1-year retention
Alerts & budgets
Enterprise
Custom
Unlimited
Self-hosted option
SSO & audit logs
📅 Build Timeline
Week 1
SDK core: wrap OpenAI/Anthropic clients, capture events, batch upload to API
Week 2
Dashboard: real-time cost chart, per-model breakdown, prompt explorer
Week 3
Polish: alerts, budget limits, public landing page, Hacker News launch
02
MCP Hub
An npm-style registry and marketplace for Model Context Protocol servers. Search, publish, discover, and one-click install MCP servers — because right now, finding MCP servers is like finding npm packages in 2010: scattered across random GitHub repos.
⏱ MVP: 1–2 weeks 🎯 First-mover advantage 📈 Traction: Network effects
💡 The Problem

MCP (Model Context Protocol) is exploding right now. Anthropic created it, Cursor adopted it, every AI tool is integrating it. But there's no central place to discover MCP servers.


Developers are sharing servers in GitHub READMEs, Discord messages, and Twitter threads. It's like npm before npmjs.com existed — a massive ecosystem with no front door.

🌟 Why Now
  • MCP adoption is in its "gold rush" phase — adoption curve is near-vertical
  • Every major AI company (Anthropic, OpenAI, Google) is moving toward tool-use protocols
  • First mover wins for registries — npm, Docker Hub, Homebrew all prove this pattern
  • The protocol is standardized, but discovery is completely fragmented
🔧 How It Works
  • Searchable catalog — browse by category (databases, APIs, dev tools, cloud providers)
  • GitHub integration — auto-index repos with MCP server manifests, pull README, stars, activity
  • One-click install — generate the config snippet for Cursor, Claude Desktop, etc.
  • Quality signals — download count, verified badge, compatibility matrix, user reviews
🚀 Go-to-Market
  • Pre-populate by scraping every MCP server from GitHub (there are already 1,000+)
  • Submit to Anthropic — get listed as "community resource" in their MCP docs
  • SEO play — "mcp server for [X]" is an untapped search gold mine
  • Community flywheel — every new server listed makes the registry more valuable
📈 Competitive Landscape
Feature GitHub Search Awesome Lists MCP Hub (Ours)
Search by category Barely Manual scroll Full-text + filters
One-click install No No Yes — config snippet
Quality signals Stars only Curated (slow) Stars + downloads + verified
Auto-update listings N/A Manual PRs GitHub webhook sync
Publish workflow Just push code Submit PR CLI publish + auto-detect
terminal — publishing a server
# Publish your MCP server to the registry $ npx mcphub publish ✔ Detected MCP server manifest (mcp.json) ✔ Validated 12 tools, 3 resources ✔ Published @yourname/postgres-mcp v1.2.0 ✔ Live at https://mcphub.dev/p/yourname/postgres-mcp # Install any server with one command $ npx mcphub install @stripe/mcp-server --target cursor ✔ Added to .cursor/mcp.json ✔ Restart Cursor to activate
🛠 Recommended Tech Stack
Next.js 14 TypeScript Postgres GitHub API Algolia / Meilisearch Tailwind CSS Vercel
💰 Revenue Model
Free forever
$0
Unlimited browsing
Publish public servers
Community support
Verified Publisher
$19/mo
Verified badge
Analytics dashboard
Priority listing
Sponsored Listing
$99/mo
Featured placement
Category sponsorship
Analytics + leads
📅 Build Timeline
Week 1
Scrape GitHub for existing MCP servers, build searchable catalog with Next.js, deploy to Vercel
Week 2
Add publish CLI, one-click install configs, user accounts, submit to Anthropic docs for listing
03
ShieldReview
A GitHub App that auto-reviews every PR for security vulnerabilities — not generic "AI code review" but laser-focused on catching secrets, injection flaws, auth bypasses, and dependency risks. Published on GitHub Marketplace for instant distribution to millions of developers.
⏱ MVP: 1–2 weeks 🎯 GitHub Marketplace distribution 📈 Traction: Free for public repos
💡 The Problem

Generic AI code reviewers (CodeRabbit, Codium, etc.) try to do everything — style, logic, performance, security. The result? Noisy, generic comments that developers learn to ignore.


Security review needs to be specialized and trusted. A tool that only comments when it finds a real vulnerability gets respect. A tool that comments on everything becomes noise.

🌟 Why Now
  • Supply chain attacks are up 742% since 2022 — security is top of mind for every CTO
  • AI models in 2026 are finally good enough to reason about security patterns reliably
  • GitHub Marketplace gives you instant distribution to 100M+ developers
  • "Shift left" security is a $7.5B market and growing — but tooling is enterprise-only
🔧 How It Works
  • GitHub App — installs in 2 clicks, triggers on every PR
  • Diff analysis — only scans changed lines (fast, cheap, focused)
  • AI-powered reasoning — uses Claude/GPT-4o to reason about security context, not just pattern match
  • Actionable comments — inline suggestions with fix code, severity rating, CVE references
  • Zero false-positive culture — only comments when confidence is high, earns developer trust
🚀 Go-to-Market
  • GitHub Marketplace — free for public repos, paid for private (instant distribution)
  • Security-first positioning — "The AI security reviewer that only speaks when it matters"
  • Case studies — scan popular open-source repos, report found vulnerabilities, build credibility
  • SOC 2 angle — "Add ShieldReview to your PR workflow" as a compliance checkbox
PR #247 — ShieldReview comment
// ShieldReview found 1 issue in this PR ⚠️ HIGH — SQL Injection in src/api/users.ts:42 const query = `SELECT * FROM users WHERE id = ${req.params.id}` ^^^^^^^^^^^^^^^^^ User input is interpolated directly into SQL query. This allows an attacker to extract or modify any data in the database. Suggested fix: const query = `SELECT * FROM users WHERE id = $1` const result = await db.query(query, [req.params.id]) References: CWE-89, OWASP A03:2021
🛡️ What It Catches (v1 Scope)
  • Hardcoded secrets & API keys
  • SQL/NoSQL injection patterns
  • XSS vulnerabilities
  • Insecure deserialization
  • Authentication bypasses
  • Path traversal attacks
  • Insecure cryptography usage
  • Dependency vulnerabilities (via OSV)
  • SSRF & open redirect
  • Missing rate limiting
  • Privilege escalation patterns
  • Unsafe file uploads
🛠 Recommended Tech Stack
Node.js TypeScript Probot (GitHub App framework) Claude API / GPT-4o Redis (rate limiting) Railway / Vercel
💰 Revenue Model
Open Source
$0
Public repos
Unlimited PRs
Community support
Pro
$19/mo
Private repos
Up to 5 repos
Slack notifications
Team
$49/mo
Unlimited repos
Custom rules
Dashboard & trends
Enterprise
$199/mo
Self-hosted
SAML/SSO
Compliance reports
📅 Build Timeline
Week 1
GitHub App with Probot, PR webhook listener, diff parser, AI analysis pipeline with Claude
Week 2
Inline PR comments, severity ratings, suggested fixes, publish on GitHub Marketplace
The Verdict
If you can only build one thing...
All three are viable, but here's the honest ranking for a solo developer in March 2026.
🥇 MCP Hub — Build This First

Smallest MVP, biggest timing advantage.

  • Literally a searchable catalog — ship in days, not weeks
  • MCP is in its gold rush phase RIGHT NOW — this window closes fast
  • First-mover advantage is real for registries (npm, Docker Hub, crates.io)
  • Network effects compound — every new server makes your registry more valuable
  • SEO alone could drive thousands of daily visitors within months
🥈 LLM Radar — Build This Second

Biggest revenue potential, needs more polish.

  • Solves a real, painful problem — teams are bleeding money on LLM APIs
  • Open-source SDK is a strong distribution moat
  • Clear path to $29-99/mo subscriptions
  • Takes 2-3 weeks but the payoff is higher long-term
🥉 ShieldReview — Build This Third

Best distribution, most competitive market.

  • GitHub Marketplace is unmatched distribution
  • Security niche is defensible — but more crowded than the other two
  • Can differentiate with zero-false-positive philosophy
  • Enterprise upsell path is strong if you get trust
The Strategy: Build Sequentially, Compound Distribution

Ship MCP Hub in 1-2 weeks. Use the audience and credibility to launch LLM Radar. Use the open-source community from both to launch ShieldReview on GitHub Marketplace. Each product feeds the next. This is how solo devs build empires.

Ready to start building?

These aren't theoretical ideas. They're specific, actionable products with clear paths to traction. Pick one and ship it this month.

Start with MCP Hub ↑