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recon
35× fewer tokens for AI coding agents
Local-first MCP server for AI coding agents. A 24 MB Rust binary that replaces Read, Grep, and Glob with 12 symbol-aware tools — 15–35× token reduction, 8 ms queries on 320K symbols. Your code never leaves your machine.
Most AI coding agents burn 95% of their context window on Read, Grep, and Glob. They read entire files, grep across the whole repo, and glob every match — when all you needed was one function. 23,838 tokens to find one function. The same answer fits in 681.
I built recon to fix this. It's a 24 MB local-first MCP server in Rust that gives your agent twelve symbol-aware tools — find_symbol, outline, skeleton, repo_map, etc. — instead of bulk file reading. Tree-sitter for parsing, Tantivy for search, SQLite for the index. p99 query latency is ~8 ms on 320K symbols.
Setup is three steps: 1. Sign in with GitHub 2. recon login 3. recon init --mcp <ide> // claude , opencode , cursor , windsurf
Then your agent does the rest — recon writes the MCP config for whichever IDE you use and adds a strict policy file telling the model to prefer the symbol-aware tools.
Now available on Claude Code, opencode, Cursor, and Windsurf.
Why it matters: - Code never leaves your machine. Your repo is indexed locally; only license validation hits the cloud. - 9 languages indexed (Rust, TS, JS, Python, Go, Java, C/C++, Ruby) via tree-sitter. - File save → queryable in <1 s. - Free tier: 1 repo, 250 files, 10K LOC. Pro: 10 repos, 5,000 files/repo, 200K LOC. No credit card to start.
Honest first-launch admission: the .pages.dev URL is on the Cloudflare shared-subdomain TLD, which some link previewers (LinkedIn especially) flag defensively. A custom domain is in flight. If a link warns you, copy it into the address bar.
Try it: https://mcprecon.pages.dev/ Genuinely curious what breaks for you. The hardest part of building this was making sure the agent actually reaches for the symbol-aware tools instead of falling back to its trained Read/Grep prior— would love to hear how it lands in your IDE.
— bravo1goingdark
About recon on Product Hunt
“35× fewer tokens for AI coding agents”
recon was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #99 on the daily leaderboard. Local-first MCP server for AI coding agents. A 24 MB Rust binary that replaces Read, Grep, and Glob with 12 symbol-aware tools — 15–35× token reduction, 8 ms queries on 320K symbols. Your code never leaves your machine.
On the analytics side, recon competes within Productivity, Developer Tools and Artificial Intelligence — topics that collectively have 1.6M followers on Product Hunt. The dashboard above tracks how recon performed against the three products that launched closest to it on the same day.
Who hunted recon?
recon was hunted by Ashutosh Kumar. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of recon including community comment highlights and product details, visit the product overview.
Ashutosh Kumar
Hey Product Hunt 👋
Most AI coding agents burn 95% of their context window on Read, Grep, and Glob. They read entire files, grep across the whole repo, and glob every match — when all you needed was one function.
23,838 tokens to find one function. The same answer fits in 681.
I built recon to fix this. It's a 24 MB local-first MCP server in Rust that gives your agent twelve symbol-aware tools — find_symbol, outline, skeleton, repo_map, etc. — instead of bulk file reading. Tree-sitter for parsing, Tantivy for search, SQLite for the index. p99 query latency is ~8 ms on 320K symbols.
Setup is three steps:
1. Sign in with GitHub
2. recon login
3. recon init --mcp <ide> // claude , opencode , cursor , windsurf
Then your agent does the rest — recon writes the MCP config for whichever IDE you use and adds a strict policy file telling the model to prefer the symbol-aware tools.
Now available on Claude Code, opencode, Cursor, and Windsurf.
Why it matters:
- Code never leaves your machine. Your repo is indexed locally; only license validation hits the cloud.
- 9 languages indexed (Rust, TS, JS, Python, Go, Java, C/C++, Ruby) via tree-sitter.
- File save → queryable in <1 s.
- Free tier: 1 repo, 250 files, 10K LOC. Pro: 10 repos, 5,000 files/repo, 200K LOC. No credit card to start.
Honest first-launch admission: the .pages.dev URL is on the Cloudflare shared-subdomain TLD, which some link previewers (LinkedIn especially) flag defensively. A custom domain is in flight. If a link warns you, copy it into the address bar.
Try it: https://mcprecon.pages.dev/ Genuinely curious what breaks for you. The hardest part of building this was making sure the agent actually reaches for the symbol-aware tools instead of falling back to its trained Read/Grep prior— would love to hear how it lands in your IDE.
— bravo1goingdark