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Engram - MCP Server for AI Dev Agents
Stop burning tokens. Make your agents up to 6x faster.
Engram gives AI coding agents a live, queryable, and super-intelligent unified context layer via MCP tools so they stop re-reading files on every task and start writing code immediately. get_context_for_task, get_symbol, blast-radius analysis, call graphs, and 12 more tools. 100% local by default. Works with Claude, Cursor, and any MCP-compatible agent.
I built Engram because I kept watching Claude burn thousands tokens just orienting itself at the start of every session rereading the same files over and over before writing a single line of code. The fix was a persistent graph that lives alongside your codebase. Instead of reading files, the agent calls get_context_for_task and gets exactly the information it needs, every single times.
Happy to answer any questions about how the graph works or MCP integration!
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About Engram - MCP Server for AI Dev Agents on Product Hunt
“Stop burning tokens. Make your agents up to 6x faster.”
Engram - MCP Server for AI Dev Agents was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #102 on the daily leaderboard. Engram gives AI coding agents a live, queryable, and super-intelligent unified context layer via MCP tools so they stop re-reading files on every task and start writing code immediately. get_context_for_task, get_symbol, blast-radius analysis, call graphs, and 12 more tools. 100% local by default. Works with Claude, Cursor, and any MCP-compatible agent.
Engram - MCP Server for AI Dev Agents was featured in Developer Tools (511.7k followers), Artificial Intelligence (467.3k followers) and Vibe coding (424 followers) on Product Hunt. Together, these topics include over 157.9k products, making this a competitive space to launch in.
Who hunted Engram - MCP Server for AI Dev Agents?
Engram - MCP Server for AI Dev Agents was hunted by Kabir Tiwari. 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.
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Kabir Tiwari