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

ocal-first CLI asset tracker for overseas stock investors. Tracks portfolio P\&L, net worth, and cash flow. Pulls earnings, insider trades, and SEC filings via Finnhub. 13 MCP tools for Claude Desktop — read and write your financial data in natural language.

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 users to search locally across imported Claude, ChatGPT, and Claude Code conversations and retrieve surrounding turns with citations, while keeping indexing and storage on their own computer.

Provides an external context buffer so a local model can maintain session memory across long tasks and search and page through large documents without loading them whole into its limited context window.

Aggregator MCP proxy that collapses N downstream MCP servers into 4 meta-tools with progressive tool discovery, and compresses large tool outputs (HTML→Markdown, JSON summarization) with full-output retrieval via read_more and a per-session token-savings report.

Durable project-memory MCP: decisions, constraints, and pipelines across Claude sessions

Deterministic, local-first context optimization for AI coding agents. Automatically compresses raw development session data (messages, tool logs, error stack traces, and git diffs) into a compact, task-specific context window. Operates 100% locally with zero external LLM dependencies, ensuring your source code never leaves your machine.

A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.

Local-first memory for AI agents about the people in your life. MCP server + CLI on SQLite. Never phones home.

Sovereign, deterministic, local-first context and DAG lifecycle engine with native stdio MCP server for autonomous AI coding agents.

Read-only repository context explorer for coding agents. Provides repository exploration tools via CLI or MCP adapter.

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.

Automatically captures project state on git commits, detects context drift, and delivers structured token-budgeted briefings to AI agents, ensuring project continuity without manual effort.

MCP server that validates AI-generated 1C:Enterprise (BSL) code against the real platform API. Catches unknown enum values, wrong argument counts, and missing type members by parsing the platform syntax-helper (shcntx_ru.hbk) — independent Rust implementation with built-in expression validator.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.

Provides redacted access to a private local knowledgebase for coding agents, allowing them to inspect files while hiding sensitive names and identifiers.

MCP server providing lossless file reads with deduplication, per-repo token metering, and HMAC-signed context receipts. Enables auditable, vendor-neutral measurement of what an AI agent saw.

Fantasy Premier League stats and press coverage for AI agents: read-only SQL over FPL player, fixture and gameweek data, plus semantic search over BBC Sport and Guardian articles and FPL injury news. Bring your own PostgreSQL and Pinecone, with bundled ingestion jobs.

Enables AI coding agents to reduce token usage by condensing source code into AST skeletons, extracting specific symbols, compressing logs, and estimating token budgets.

Exposes tools for AI assistants to query a persistent SQLite+FTS5 index of C/C++ symbols parsed from real build commands, enabling sub-millisecond lookup, full-text search, and natural-language explanation without hallucination.

MCP server that inspects local codebases and generates source-grounded context packs for coding agents, with tools for repository search, symbols, dependencies, Git analysis, and context generation.

Persistent project context (AGENTS.md), cross-session memory, and identity — discoverable by any MCP client.

Provides persistent tool context that survives across Claude Desktop chat sessions, automatically injecting tool-specific rules, syntax preferences, and best practices. Eliminates the need to re-establish context in each new conversation.

Enables multiple AI agents to share an append-only context store where they checkpoint work, record failures, claim files, hand off tasks, and recover interrupted sessions. It provides a single-file, multi-process-safe server so the next agent can continue where the last one stopped.

Lets AI coding agents ask a Rails app about itself: 35 read-only tools answer from the schema, models, routes, controllers, views, jobs and conventions, over MCP or the command line, even when the app cannot boot.

Read-only MCP server that exposes governed operational records with provenance and validity windows so clients can check which evidence is still current before answering. It lets agents reconcile freshness, schedule state, and evidence specificity to determine whether scheduled automations are actually healthy, rather than trusting an expired dashboard summary.

Enables users to audit personal reading streams by quantifying category diversity with Shannon entropy, detecting lexical redundancy and echo chambers via Jaccard similarity, and ranking content sources by decibel signal-to-noise ratio for pruning recommendations.

Graph RAG based context management engine for coding agents

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

Enables AI agents to access real-time Windows PC context including active window, system performance, screen time, productivity analytics, and historical usage through MCP tools.