devrecall
About
Local-first developer activity aggregator — Git, PRs, Jira, Confluence, Slack, Calendar — exposed as an MCP server so coding agents can search and cite past work
Explore
Setup
Install devrecall in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/pavelpilyak/devrecall
Follow the installation instructions in the repository README, then restart your MCP client.
Your developer activity, aggregated on-device.No cloud sync. No telemetry. Your data never leaves your machine.
DevRecall pulls from Git, Slack, Google Calendar, Jira, Linear, Confluence, and GitHub/GitLab/Bitbucket; stores it in a local SQLite database; and turns it into standups, weekly reports, brag docs, and a chat that actually knows what you worked on.
📚docs.devrecall.dev— install, configure, integrations, CLI reference.
- Local-first.SQLite on your laptop. Tokens in~/.devrecall/tokens/(0600). The Cloudflare Worker relay is a pass-through for OAuth callbacks only — it never sees your data.
- LLM-optional.Bundled embeddings run offline (ONNX +all-MiniLM-L6-v2). Use local Ollama for chat, or bring your own OpenAI/Anthropic key.
- Open source.MIT-licensed. Audit it, fork it, build it from source.
brew install --cask pavelpilyak/devrecall/devrecall
InstallsDevRecall.appand puts thedevrecallCLI on yourPATH.
git clone https://github.com/pavelpilyak/devrecall.git cd devrecall make build # → bin/devrecall
Requires Go 1.22+ with CGO enabled (for SQLite FTS5).
Then connect a source and generate your first standup:
devrecall auth github # or: slack, google, jira, linear, gitlab, bitbucket devrecall standup
Full install + setup walkthrough atdocs.devrecall.dev/install.
make build # bin/devrecall make test # tests with race detector make lint # golangci-lint
Build tags:fts5enables SQLite full-text search;GOenables hugot's pure Go ONNX backend for embeddings.
The desktop app (Tauri + Svelte) lives indesktop/; the OAuth callback relay (Cloudflare Worker) inrelay/.
Bug reports and collector contributions are especially welcome. SeeCONTRIBUTING.md.
Local code-knowledge graph + bi-temporal mistakes memory for AI coding agents. Serves a ranked structural packet instead of whole files on read/grep, and surfaces fixes your repo already reverted (mined from git history). Zero cloud, Apache-2.0.
projectmem is a local-first memory layer for AI coding agents (MCP server) — it captures issues, attempts, fixes, and decisions, then warns at git commit before you repeat a mistake. Python, runs locally, works with Claude, Cursor, Antigravity, and Codex
Self-hosted MCP server + dashboard that gives agents shared memory over a git-backed folder of markdown.
Rust MCP server that gives AI coding agents architectural awareness — persistent knowledge graph, blast radius analysis, co-change detection via git, and local semantic search. No API keys, runs entirely on-premise.
A MCP server that connects with LangChain Checkpointers, Memory Stores to aid in monitoring and observability during development of AI Applications
Local-first, state-centric memory for coding agents — remembers your project's conventions and how you like to work. 100% local, over MCP
OpenMemBrain is the intelligent membrane for AI coding memory. It autonomously reads and learns from your coding sessions — you never have to tell it what to save. It selectively absorbs project knowledge, blocks secrets, filters noise, resolves conflicts, and persists only what matters.
Persistent AI memory across tools — remember your preferences, code standards, and decisions across Claude Code, Cursor, Codex, and any MCP tool. Local-first, zero-cloud.
Provides local repo-intelligence by indexing source, symbols, call graphs, Git/GitHub history, and source-bound repo memories into a local database for coding agents.
Official Atlassian MCP server for connecting AI agents to Jira, Confluence, Opsgenie, and other Atlassian products.
Sign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.
