Sponsored by Deepsite.site

Tag

#claude

723 results found

Scratchpad Mcp

scratchpad-mcp is an MCP server that gives AI agents persistent, token-efficient storage. It solves a specific waste problem: agents constantly re-read files they've already seen, re-summarize documents they've already processed, and re-load context they've already understood. Every one of those round-trips burns tokens for no new information. This server fixes that with eight tools designed around how agents actually work: Versioned writes. write_file automatically versions every write and keeps the 10 most recent versions per file. Storage is append-only on success and atomic on failure partial writes can't corrupt state. Structured diffs. read_file accepts a since_version parameter and returns a JSON line-diff against that prior version instead of the full content. Agents that have already seen v1 can ask "what changed in v3?" and get a small structured payload they can reason about, not the entire file again. Append-only logs. append_log and read_log give agents an event-stream they can replay. Cursor-based pagination (since_entry + last_entry_id + has_more) means an agent can checkpoint where it left off and resume cheaply. On-demand summaries. summarize_file calls Claude Haiku to summarize files over ~2000 estimated tokens. Summaries are cached per file version, so repeat calls on an unchanged file cost nothing. The threshold is enforced server-side you can't accidentally pay to summarize something small. Per-agent isolation. Every operation is scoped by an agent_id parameter, so one server instance can serve many agents without leaking state between them. Storage limits. 1 MB per file write, 64 KB per log entry, 1000 files / 100k log entries / 100 MB total per agent sane multi-tenant guardrails out of the box. Backed by a single SQLite file (Postgres migration is on the roadmap). All SQL is parameterized, paths are validated against a strict allowlist, and the security model is documented honestly it's safe for one-user-per-process deployments today, and the V2 plan derives agent_id from the caller's API key for true multi-tenancy. Build agents that remember what they've already seen.

Petro Mcp

petro-mcp — Petroleum Engineering MCP Server petro-mcp exposes petroleum engineering workflows to Claude and other MCP-compatible LLMs through natural language. Instead of writing Python scripts, just ask your AI assistant. Capabilities (80+ tools across the full upstream workflow): - Well Logs (LAS): Parse LAS files, extract curves and headers, compute Vshale, porosity (density, neutron-density, sonic, effective), water saturation (Archie, Simandoux, Indonesian), permeability (Timur, Coates), and net pay. - Decline Curve Analysis: Arps exponential/hyperbolic/harmonic fits, advanced models (Duong, PLE, SEPD), EUR calculation, Monte Carlo EUR distributions, bootstrap confidence intervals, probabilistic forecasts, price sensitivities. - Rate Transient Analysis (RTA): Agarwal-Gardner, Blasingame, NPI, flowing material balance, normalized rate, sqrt-time, material balance time, permeability estimation, radius of investigation. - Production Analytics: CSV production data queries, trend analysis, anomaly detection (shut-ins, rate jumps, water breakthrough, GOR blowouts), producing ratios (GOR, WOR, water cut). - PVT & Reservoir: Black-oil correlations (Standing, Beggs-Robinson, Hall-Yarborough, Lee-Gonzalez-Eakin, Sutton), brine PVT, bubble point, oil compressibility, gas Z-factor, volumetric OOIP/OGIP, recovery factors, Havlena-Odeh, P/Z analysis. - Drilling & Wellbore: Hydrostatic pressure, ECD, kill mud weight, MAASP, burst/collapse pressure, bit pressure drop, nozzle TFA, annular velocity, dogleg severity, vertical section, well survey, anticollision, wellbore tortuosity. - Production Engineering: Nodal analysis (Vogel IPR + VLP), Beggs-Brill multiphase flow, choke flow, erosional velocity, Turner/Coleman critical rates, hydrate temperature/inhibitor, ICP/FCP, HPT. - Economics: NPV, IRR, payout period, PV10, breakeven price, well economics, operating netback, price sensitivity. - Units: Oilfield unit conversions across pressure, rate, volume, length, density, viscosity, and more. Why petro-mcp? Purpose-built for petroleum engineers. Other energy MCP servers focus on commodity prices; this one runs the actual engineering calculations — log interpretation, decline analysis, reservoir engineering, drilling, production, and economics — all through plain English. Install: pip install petro-mcp → configure in Claude Desktop → ask away. Links: GitHub: https://github.com/petropt/petro-mcp · PyPI: https://pypi.org/project/petro-mcp/ · Web tools: https://tools.petropt.com License: MIT · Author: Groundwork Analytics