Agent Recall vs Sequential Thinking

A side-by-side look at the Agent Recall and Sequential Thinking MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

Agent Recall logoAgent RecallKnowledge & Memory · Local subprocess (stdio)Correction-first agent memory. Precision KPI tracks if agents heed warnings. 5 layers, local-only.69GreatAuth: no auth requiredSequential Thinking logoSequential ThinkingKnowledge & Memory · Local subprocess (stdio)Dynamic and reflective problem-solving through thought sequences.90ExcellentAuth: no auth required

Verdict: choose Agent Recall for knowledge & memory work as a local process; choose Sequential Thinking for knowledge & memory as a local process. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

Agent Recall logoChoose Agent Recall when

  • You need dedicated capabilities in the Knowledge & Memory domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: No auth required.
  • You want tools like session_start, session_end, remember.
Explore Agent Recall

Sequential Thinking logoChoose Sequential Thinking when

  • You need dedicated capabilities in the Knowledge & Memory domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: No auth required.
  • You want tools like create_entities, create_relations, add_observations.
Explore Sequential Thinking

Feature & specification comparison

Rows where the two servers differ are marked.

SpecAgent Recall logoAgent RecallSequential Thinking logoSequential Thinking
CategoryKnowledge & MemoryKnowledge & Memory
Quality signal69/100 · Great90/100 · Excellent
Install commandConfirmedConfirmed
TransportLocal subprocess (stdio)Local subprocess (stdio)
AuthNo auth requiredNo auth required
PricingFreeFree
Required env varsNone listedNone listed
Verified ownerCommunity listing Verified
GitHub stars37191,405
Directory activity 3 views 0 installs 0 upvotes 4 views 3 installs 0 upvotes
Tools59

Tools & capabilities

Agent Recall tools 5

  • session_start[ENTRY — call FIRST, before acting] Use when the user asks to start, load, continue, resume, or open memory for a project. Set mode='lite' for a ≤500-token briefing (good for fresh conversations where the agent will pull memory on demand via recall()).
  • session_end[ON SAVE/EXIT — YOU must call this; nothing auto-saves] Use when the user asks to save, checkpoint, summarize, end, retain, or persist the current session. Optionally pass close_phase / open_phase to update the project pipeline narrative spine in the same call.
  • remember[MID-SESSION WRITE — single fact/decision; saying it is not saving it] Use when the user asks to remember, store, note, or save a specific decision, fact, or insight.
  • recall[RETRIEVE — use freely, any time] Use when the user asks to recall, search, find, or look up previous memory, context, or decisions.
  • check[MID-SESSION — safe any time; for alignment, before risky decisions] Use when the user asks to validate understanding, verify alignment, or check if their interpretation matches the human's intent. Also call BEFORE a high-risk action — publish, deploy, delete, credential exposure, external send/message, or any other irreversible write — passing `action_description` (one sentence, what you're about to do). Returns matching corrections/rules/insights plus a `verdict`: `blocked` means an authoritative correction OVERRIDES the plan — read it before proceeding. To RECORD a durable human correction, pass `human_correction` as the STRUCTURED object {rule, why, applies_when} — a plain string is only STAGED for later review, never activated.

Sequential Thinking tools 9

  • create_entitiesCreate multiple new entities in the knowledge graph
  • create_relationsCreate multiple new relations between entities in the knowledge graph. Relations should be in active voice
  • add_observationsAdd new observations to existing entities in the knowledge graph
  • delete_entitiesDelete multiple entities and their associated relations from the knowledge graph
  • delete_observationsDelete specific observations from entities in the knowledge graph
  • delete_relationsDelete multiple relations from the knowledge graph
  • read_graphRead the entire knowledge graph
  • search_nodesSearch for nodes in the knowledge graph based on a query
  • open_nodesOpen specific nodes in the knowledge graph by their names

Ready-to-paste client configs

Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.

Agent Recall

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "agent-recall": {
      "command": "npx",
      "args": [
        "-y",
        "agent-recall-mcp"
      ]
    }
  }
}

Sequential Thinking

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "sequential-thinking": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-memory"
      ]
    }
  }
}

Frequently asked questions

Agent Recall is categorized under Knowledge & Memory and uses a local stdio subprocess. Sequential Thinking belongs to Knowledge & Memory and uses a local stdio subprocess. Pick Agent Recall for knowledge & memory work and Sequential Thinking for knowledge & memory.

Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.

Agent Recall is listed as free. Auth: no auth required. Sequential Thinking is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.

Yes. MCP clients support multiple servers: add agent-recall and sequential-thinking as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, Agent Recall has a quality signal of 69/100 (Great) with 3 views, 0 installs and 371 GitHub stars. Sequential Thinking has 90/100 (Excellent) with 4 views, 3 installs and 91,405 GitHub stars.