"MCP server for saving context and ensuring project consistency" matching MCP servers:

It enables users to interact with a codebase through hybrid retrieval, code graph navigation, impact analysis, and context preparation for AI coding agents.

Enables Codex to submit, poll, and retrieve bounded text handoffs for durable image-generation and image-inspection jobs while keeping provider-returned media bytes outside the MCP boundary.

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

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

Enables persisted image generation and inspection jobs through bounded MCP tools, returning only compact text handoffs, hashes, relative references, and Job IDs while keeping provider-returned media outside public results.

Enables Codex to run image generation and inspection as durable, restart-reconcilable local jobs that keep provider-returned media behind the tool boundary and hand back only bounded text, hashes, relative references, and Job IDs. It also supports idempotent submission, job history, and an offline deterministic mock provider for validating transport and persistence behavior without spending API credits.

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.

Enables AI project feasibility evaluation and solution planning through structured reasoning stages, using Gemini API and web search for up-to-date research.

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.

Enables MCP clients to discover OpenRouter image and video models, generate and edit images, create variations, launch and monitor video jobs, and save resulting media into authorized local project directories with cost controls.

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.

Enables OpenAI-compatible clients to access external tools, APIs, repositories, and data sources through MCP with allowlisting, approval, and argument validation, deployable as a FastAPI service or Python library.

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 natural-language arithmetic operations such as addition, subtraction, multiplication, and division through an MCP server connected to a LangChain client using Groq.

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.

MCP server for deterministic context preflight, token counting, and credential redaction for coding agents, with a free local tier up to 12,000 characters and paid HTTP fallback for larger inputs.

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 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.