"Information about 'Firma' and Its Context" matching MCP servers:

Provides current weather information for any location and generates AI-powered responses using Google Gemini through FastMCP.

MCP server that cuts cloud LLM costs 36-42% by indexing context locally and giving agents precision retrieval tools instead of raw context dumps.

Proxy for OpenAI-compatible backends that compacts conversation history before the context window fills, with read-only MCP tools to search and read back the archived originals.

Long AI conversations fail in predictable ways. Context-First fixes all four: Failure Mode What Goes Wrong Context-First Solution Context Drift AI forgets earlier decisions and intent as the conversation grows context_loop + detect_drift continuously re-anchor every turn Silent Contradiction New inputs silently overrule established facts — the AI doesn't notice detect_conflicts compares every inp

Imports private ChatGPT conversations into MCP clients like Codex and Claude Code. Provides tools to fetch remote conversation content and serve cached context via local stdio.

MCP server providing virtual memory for AI context with durable SQLite storage, retrieval, and bounded prompt assembly to manage context windows.

A context window optimizer and session rotator MCP server for agentic workflows that prevents LLMs from running out of context by compacting chat history and rotating sessions.

Enables Codex to run durable, context-bounded image generation and inspection jobs through local MCP tools, returning compact text results, hashes, relative references, and Job IDs instead of media bytes.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Provides LLMs with persistent memory and reusable skills via MCP, enabling semantic storage and retrieval of user preferences, project context, and step-by-step procedures across conversations.

A daily feed of AI releases, tools and techniques, each with a verification status, source trust score and evidence links. Read-only MCP server, no sign-in or keys.

Enables text-only coding models to read images, PDFs, presentations, spreadsheets, and other non-text files through a single analyze_media tool, combining local document extraction, OCR, and optional vision models with clear evidence labeling.

Enables Codex to run context-bounded image generation and inspection as durable local jobs, returning bounded text handoffs, hashes, relative references, and Job IDs while keeping provider-returned media bytes outside the MCP boundary.

Enables AI coding agents to retrieve the exact original tool-output slices omitted during lossless context compression, via on-demand expansion of hashed references stored in a shared cross-process SQLite vault. Tracks expansion overhead so agents and users can measure true net token savings across debugging sessions.

Enables Codex to run durable, context-bounded image generation and inspection jobs that return only bounded text handoffs, hashes, relative references, and Job IDs instead of media bytes. Supports idempotent submission, restart reconciliation, and optional OpenAI-backed generation and inspection.

Enables offline, read-only forensic analysis of Claude Code session transcripts, providing exact token usage, cost estimates, context growth, and compaction suggestions.

Enables Claude to offload code generation to Google's Gemini, saving tokens by writing files directly to disk without returning the content to the chat.

Enables Codex to run image generation and inspection as durable, resumable local jobs whose provider-returned media bytes stay behind the MCP boundary. Callers receive only bounded text handoffs, hashes, relative references, and Job IDs instead of pixels, keeping image-heavy workflows context-bounded.

Enables Codex to run context-bounded image generation and inspection as durable local jobs, returning only bounded text handoffs, hashes, relative references, and job IDs while keeping media bytes behind the MCP boundary.

Enables AI agents like Claude and Cursor to query codebases using Augment's context engine via the Auggie CLI.

Enables Codex to run image generation and inspection as durable, idempotent local jobs that return only bounded text handoffs, hashes, relative references, and Job IDs while keeping provider media bytes behind the MCP boundary. This keeps image-heavy workflows context-bounded, restart-safe, and resumable across multiple concurrent Codex tasks.

Paid hosted MCP server for OpenAI Codex context compression, providing tools to compress context, estimate savings, issue receipts, and read history.

Enables Codex to run image generation and inspection as durable, context-bounded local jobs, returning only bounded text handoffs, hashes, relative references, and Job IDs while keeping provider media bytes outside the public MCP boundary.

Enables Codex to run image generation and inspection as durable, resumable local jobs while keeping provider-returned media bytes outside the MCP boundary. Returns only bounded text handoffs, hashes, relative artifact references, and Job IDs so image-heavy workflows stay context-bounded.

Enables Codex to run context-bounded image generation and inspection as durable local jobs, returning only bounded text handoffs, hashes, relative references, and Job IDs while keeping media bytes outside the task context.

Enables Codex workflows to submit context-bounded image generation and inspection as durable local jobs, keeping provider-returned media bytes outside the MCP result boundary and returning only bounded text handoffs, hashes, relative references, and Job IDs.

Enables coding agents to preserve and recover structured task state across context loss, recording objectives, constraints, decisions, and plan, and reconstructing a bounded deterministic context block on session resume.

Enables Codex to run image generation and inspection as durable, restart-safe local jobs while keeping provider-returned media behind the tool boundary, returning only bounded text handoffs, hashes, relative artifact references, and Job IDs. This keeps image-heavy workflows context-bounded, resumable, and free of image bytes or base64 data in the public results.

This MCP server enables Codex to run image generation and inspection as durable local jobs, returning bounded text handoffs, hashes, relative references, and job IDs instead of media bytes.

Enables Codex to run image generation and inspection as durable, resumable local jobs whose media bytes stay behind the MCP boundary. Returns only bounded text handoffs, hashes, relative references, and Job IDs, optionally using an offline mock or the OpenAI Image/Responses APIs.